{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Results for random forest classifier" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "from time import gmtime, strftime\n", "\n", "import numpy as np\n", "import pandas as pd\n", "from imblearn.over_sampling import RandomOverSampler\n", "from sklearn import preprocessing\n", "from sklearn.ensemble import RandomForestClassifier\n", "from sklearn.metrics import classification_report\n", "from sklearn.model_selection import TimeSeriesSplit" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "strftime(\"%Y-%m-%d %H:%M:%S\", gmtime())\n", "\n", "# import data\n", "df = pd.read_csv(\"data/SCADA_downtime_merged.csv\", skip_blank_lines=True)\n", "\n", "list1 = list(df[\"turbine_id\"].unique()) # list of turbines to plot\n", "list1 = sorted(list1, key=int) # sort turbines in ascending order\n", "list2 = list(df[\"TurbineCategory_id\"].unique()) # list of categories\n", "list2 = [g for g in list2 if g >= 0] # remove NaN from list\n", "list2 = sorted(list2, key=int) # sort categories in ascending order\n", "list2 = [m for m in list2 if m not in (1, 12, 13, 14, 15, 17, 21, 22)]\n", "# categories to remove\n", "list4 = list(range(0, 14))\n", "list5 = list(zip(list4, list2))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 1, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 19 0.986154 0.995586 0.990848 16311\n", " 20 0.918919 0.781609 0.844720 1044\n", "\n", "avg / total 0.982110 0.982714 0.982057 17355\n", "\n", "Classification report for turbine 1, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 19 0.976265 0.996085 0.986076 15072\n", " 20 0.970157 0.840123 0.900469 2283\n", "\n", "avg / total 0.975461 0.975569 0.974814 17355\n", "\n", "Classification report for turbine 1, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 19 0.933597 0.935399 0.934497 9845\n", " 20 0.915098 0.912783 0.913939 7510\n", "\n", "avg / total 0.925592 0.925612 0.925601 17355\n", "\n", "Classification report for turbine 1, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 19 0.990683 0.994477 0.992576 13579\n", " 20 0.979860 0.966367 0.973067 3776\n", "\n", "avg / total 0.988328 0.988361 0.988331 17355\n", "\n", "Classification report for turbine 1, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 19 0.985028 0.996286 0.990625 14000\n", " 20 0.983725 0.936811 0.959695 3355\n", "\n", "avg / total 0.984776 0.984788 0.984646 17355\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 1, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 5\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.968403 0.994881 0.981463 16019\n", " 20 0.905345 0.779482 0.837713 1043\n", "\n", "avg / total 0.948264 0.965140 0.956254 17355\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 1, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 249\n", " 11 0.000000 0.000000 0.000000 192\n", " 12 0.000000 0.000000 0.000000 180\n", " 13 0.000000 0.000000 0.000000 180\n", " 14 0.000000 0.000000 0.000000 180\n", " 15 0.071429 0.006452 0.011834 155\n", " 16 0.000000 0.000000 0.000000 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.903939 0.986536 0.943433 14260\n", " 20 0.635925 0.690897 0.662272 1527\n", "\n", "avg / total 0.799326 0.871449 0.833563 17355\n", "\n", "Classification report for turbine 1, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.844371 0.906552 0.874357 9845\n", " 20 0.884068 0.686418 0.772806 7510\n", "\n", "avg / total 0.861549 0.811294 0.830413 17355\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 1, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 84\n", " 11 0.045455 0.055556 0.050000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.970482 0.986835 0.978590 13293\n", " 20 0.957805 0.941192 0.949426 3690\n", "\n", "avg / total 0.947079 0.956093 0.951517 17355\n", "\n", "Classification report for turbine 1, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 17\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.955467 0.989135 0.972010 13622\n", " 20 0.913920 0.909554 0.911732 3140\n", "\n", "avg / total 0.915303 0.940939 0.927891 17355\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 1, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.986291 0.996812 0.991523 16311\n", " 20 0.940230 0.783525 0.854754 1044\n", "\n", "avg / total 0.983520 0.983982 0.983296 17355\n", "\n", "Classification report for turbine 1, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.984193 0.995555 0.989841 15072\n", " 20 0.968231 0.894437 0.929872 2283\n", "\n", "avg / total 0.982093 0.982253 0.981952 17355\n", "\n", "Classification report for turbine 1, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.945232 0.934383 0.939776 9845\n", " 20 0.915256 0.929028 0.922091 7510\n", "\n", "avg / total 0.932261 0.932066 0.932123 17355\n", "\n", "Classification report for turbine 1, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.988873 0.994845 0.991850 13579\n", " 20 0.981050 0.959746 0.970281 3776\n", "\n", "avg / total 0.987171 0.987208 0.987157 17355\n", "\n", "Classification report for turbine 1, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.984192 0.996143 0.990131 14000\n", " 20 0.983046 0.933234 0.957492 3355\n", "\n", "avg / total 0.983970 0.983982 0.983822 17355\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 1, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.226994 0.560606 0.323144 66\n", " 11 0.015394 0.224299 0.028812 107\n", " 12 0.020468 0.097222 0.033816 72\n", " 13 0.010638 0.033898 0.016194 59\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.977245 0.804418 0.882449 16070\n", " 20 0.778761 0.358818 0.491277 981\n", "\n", "avg / total 0.949987 0.769173 0.846483 17355\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 1, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.966858 0.983280 0.975000 15072\n", " 20 0.961887 0.696452 0.807927 2283\n", "\n", "avg / total 0.966204 0.945549 0.953022 17355\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 1, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.887364 0.939462 0.912670 9845\n", " 20 0.916704 0.826498 0.869267 7510\n", "\n", "avg / total 0.900060 0.890579 0.893888 17355\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 1, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.009009 0.016260 0.011594 123\n", " 11 0.166667 0.003257 0.006390 307\n", " 12 0.000000 0.000000 0.000000 252\n", " 13 0.000000 0.000000 0.000000 252\n", " 14 0.076923 0.003968 0.007547 252\n", " 15 0.000000 0.000000 0.000000 233\n", " 16 0.000000 0.000000 0.000000 184\n", " 17 0.000000 0.000000 0.000000 180\n", " 18 0.000000 0.000000 0.000000 180\n", " 19 0.871345 0.990148 0.926955 11977\n", " 20 0.879704 0.869400 0.874521 3415\n", "\n", "avg / total 0.778562 0.854624 0.812096 17355\n", "\n", "Classification report for turbine 1, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.111111 0.053763 0.072464 93\n", " 11 0.000000 0.000000 0.000000 43\n", " 12 0.013889 0.027778 0.018519 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.959595 0.968839 0.964195 13703\n", " 20 0.945937 0.884498 0.914186 3264\n", "\n", "avg / total 0.936197 0.931662 0.933660 17355\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 1, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 10 0.590909 0.658228 0.622754 316\n", " 11 0.144444 0.125517 0.134317 725\n", " 12 0.110553 0.065282 0.082090 674\n", " 13 0.062112 0.016863 0.026525 593\n", " 14 0.033058 0.013986 0.019656 572\n", " 15 0.012766 0.005556 0.007742 540\n", " 16 0.095694 0.039139 0.055556 511\n", " 17 0.032609 0.006579 0.010949 456\n", " 18 0.000000 0.000000 0.000000 432\n", " 19 0.748451 0.905797 0.819641 12006\n", " 20 0.414254 0.350943 0.379980 530\n", "\n", "avg / total 0.558792 0.659637 0.602480 17355\n", "\n", "Classification report for turbine 1, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 10 0.255495 0.853211 0.393235 109\n", " 11 0.009901 0.022727 0.013793 88\n", " 12 0.022857 0.055556 0.032389 72\n", " 13 0.006711 0.013889 0.009050 72\n", " 14 0.029630 0.055556 0.038647 72\n", " 15 0.005780 0.013889 0.008163 72\n", " 16 0.004202 0.013889 0.006452 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.943256 0.923252 0.933147 14476\n", " 20 0.950098 0.664371 0.781951 2178\n", "\n", "avg / total 0.907957 0.859579 0.879414 17355\n", "\n", "Classification report for turbine 1, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 10 0.163158 0.607843 0.257261 51\n", " 11 0.000000 0.000000 0.000000 53\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.811115 0.766969 0.788424 9591\n", " 20 0.876472 0.783477 0.827370 7408\n", "\n", "avg / total 0.822854 0.760069 0.789632 17355\n", "\n", "Classification report for turbine 1, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 10 0.300595 0.926606 0.453933 109\n", " 11 0.006667 0.013889 0.009009 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.012048 0.013889 0.012903 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.041667 0.027778 0.033333 72\n", " 16 0.000000 0.000000 0.000000 67\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.968856 0.965942 0.967397 13301\n", " 20 0.910863 0.827336 0.867092 3446\n", "\n", "avg / total 0.925537 0.910631 0.916670 17355\n", "\n", "Classification report for turbine 1, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 10 0.050794 0.355556 0.088889 45\n", " 11 0.006928 0.041667 0.011881 72\n", " 12 0.013699 0.027778 0.018349 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.006369 0.013889 0.008734 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.954549 0.928550 0.941370 13548\n", " 20 0.923104 0.810107 0.862922 3186\n", "\n", "avg / total 0.914864 0.874849 0.893677 17355\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 1, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 19 0.986203 0.994789 0.990477 16311\n", " 20 0.905765 0.782567 0.839671 1044\n", "\n", "avg / total 0.981364 0.982022 0.981406 17355\n", "\n", "Classification report for turbine 1, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 19 0.971290 0.996616 0.983790 15072\n", " 20 0.973016 0.805519 0.881380 2283\n", "\n", "avg / total 0.971517 0.971478 0.970318 17355\n", "\n", "Classification report for turbine 1, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 65\n", " 11 0.000000 0.000000 0.000000 88\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.906679 0.922100 0.914324 9525\n", " 20 0.875196 0.935592 0.904386 7173\n", "\n", "avg / total 0.859343 0.892769 0.875604 17355\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 1, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 27\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.933324 0.993991 0.962703 12815\n", " 20 0.950556 0.937791 0.944130 3649\n", "\n", "avg / total 0.889030 0.931144 0.909373 17355\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 1, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.978938 0.992643 0.985743 14000\n", " 20 0.981266 0.905514 0.941869 3355\n", "\n", "avg / total 0.979388 0.975799 0.977261 17355\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 1, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 7\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 71\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.960965 0.991954 0.976213 15908\n", " 20 0.879271 0.765114 0.818230 1009\n", "\n", "avg / total 0.931963 0.953731 0.942391 17355\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 1, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 224\n", " 11 0.000000 0.000000 0.000000 260\n", " 12 0.111111 0.004425 0.008511 226\n", " 13 0.000000 0.000000 0.000000 211\n", " 14 0.000000 0.000000 0.000000 180\n", " 15 0.000000 0.000000 0.000000 180\n", " 16 0.000000 0.000000 0.000000 180\n", " 17 0.000000 0.000000 0.000000 180\n", " 18 0.000000 0.000000 0.000000 180\n", " 19 0.877460 0.989788 0.930245 13514\n", " 20 0.847772 0.838119 0.842918 2020\n", "\n", "avg / total 0.783383 0.868338 0.822585 17355\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 1, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.000436 0.001095 0.000623 913\n", " 11 0.001403 0.025000 0.002656 80\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.784869 0.726046 0.754312 8673\n", " 20 0.855935 0.662352 0.746803 7185\n", "\n", "avg / total 0.746619 0.637223 0.686183 17355\n", "\n", "Classification report for turbine 1, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.071429 0.007576 0.013699 132\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.960754 0.981495 0.971014 13294\n", " 20 0.941078 0.925570 0.933259 3641\n", "\n", "avg / total 0.933919 0.946067 0.939698 17355\n", "\n", "Classification report for turbine 1, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.134328 0.065217 0.087805 138\n", " 11 0.021739 0.012346 0.015748 324\n", " 12 0.000000 0.000000 0.000000 324\n", " 13 0.000000 0.000000 0.000000 324\n", " 14 0.000000 0.000000 0.000000 324\n", " 15 0.000000 0.000000 0.000000 324\n", " 16 0.000000 0.000000 0.000000 324\n", " 17 0.000000 0.000000 0.000000 324\n", " 18 0.000000 0.000000 0.000000 304\n", " 19 0.800272 0.974442 0.878811 11464\n", " 20 0.937666 0.889029 0.912700 3181\n", "\n", "avg / total 0.701966 0.807375 0.748787 17355\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 1, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.983471 0.952057 0.967509 16311\n", " 20 0.900836 0.722222 0.801701 1044\n", "\n", "avg / total 0.978500 0.938231 0.957535 17355\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 1, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 80\n", " 11 0.000000 0.000000 0.000000 109\n", " 12 0.000000 0.000000 0.000000 86\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.962751 0.979326 0.970968 14753\n", " 20 0.772947 0.844327 0.807062 1895\n", "\n", "avg / total 0.902806 0.924690 0.913516 17355\n", "\n", "Classification report for turbine 1, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 117\n", " 11 0.000000 0.000000 0.000000 144\n", " 12 0.000000 0.000000 0.000000 144\n", " 13 0.000000 0.000000 0.000000 144\n", " 14 0.000000 0.000000 0.000000 126\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.686125 0.770854 0.726026 8859\n", " 20 0.887937 0.687373 0.774887 7389\n", "\n", "avg / total 0.728283 0.686142 0.700519 17355\n", "\n", "Classification report for turbine 1, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.987764 0.986892 0.987328 13579\n", " 20 0.982369 0.944386 0.963003 3776\n", "\n", "avg / total 0.986591 0.977643 0.982035 17355\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 1, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 7\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.964912 0.990200 0.977392 13775\n", " 20 0.960935 0.913546 0.936642 3285\n", "\n", "avg / total 0.947758 0.958859 0.953065 17355\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 1, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.251121 0.315493 0.279650 710\n", " 11 0.320546 0.386434 0.350419 2919\n", " 12 0.130556 0.209121 0.160752 1798\n", " 13 0.076923 0.115836 0.092452 1364\n", " 14 0.068659 0.075488 0.071912 1126\n", " 15 0.089666 0.062967 0.073981 937\n", " 16 0.042623 0.033079 0.037249 786\n", " 17 0.046875 0.028340 0.035324 741\n", " 18 0.074212 0.059524 0.066061 672\n", " 19 0.539968 0.390352 0.453129 6074\n", " 20 0.150794 0.083333 0.107345 228\n", "\n", "avg / total 0.290822 0.259695 0.268711 17355\n", "\n", "Classification report for turbine 1, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.046386 0.349593 0.081905 123\n", " 11 0.152042 0.386740 0.218273 905\n", " 12 0.062432 0.155313 0.089062 734\n", " 13 0.025702 0.062682 0.036456 686\n", " 14 0.039565 0.064309 0.048990 622\n", " 15 0.054945 0.065359 0.059701 612\n", " 16 0.043548 0.045918 0.044702 588\n", " 17 0.038532 0.036458 0.037467 576\n", " 18 0.036585 0.028463 0.032017 527\n", " 19 0.766573 0.509219 0.611939 10196\n", " 20 0.864815 0.261478 0.401548 1786\n", "\n", "avg / total 0.558491 0.366004 0.425597 17355\n", "\n", "Classification report for turbine 1, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.014229 0.240000 0.026866 150\n", " 11 0.086643 0.127660 0.103226 376\n", " 12 0.021008 0.014245 0.016978 351\n", " 13 0.009302 0.006173 0.007421 324\n", " 14 0.021898 0.009259 0.013015 324\n", " 15 0.023438 0.009259 0.013274 324\n", " 16 0.050420 0.019417 0.028037 309\n", " 17 0.020202 0.007042 0.010444 284\n", " 18 0.010152 0.007937 0.008909 252\n", " 19 0.595705 0.602057 0.598864 7971\n", " 20 0.821133 0.623767 0.708970 6690\n", "\n", "avg / total 0.594953 0.523135 0.552588 17355\n", "\n", "Classification report for turbine 1, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.130259 0.295413 0.180797 545\n", " 11 0.207217 0.342980 0.258349 1624\n", " 12 0.078947 0.087488 0.082999 1063\n", " 13 0.061372 0.057955 0.059614 880\n", " 14 0.049531 0.056231 0.052669 658\n", " 15 0.044199 0.049922 0.046886 641\n", " 16 0.092910 0.065972 0.077157 576\n", " 17 0.047619 0.023985 0.031902 542\n", " 18 0.015267 0.008214 0.010681 487\n", " 19 0.685113 0.631830 0.657393 8602\n", " 20 0.653631 0.404145 0.499466 1737\n", "\n", "avg / total 0.444934 0.410429 0.421371 17355\n", "\n", "Classification report for turbine 1, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.273526 0.274214 0.273869 795\n", " 11 0.224557 0.396435 0.286710 2076\n", " 12 0.069261 0.069859 0.069558 1274\n", " 13 0.070362 0.064769 0.067450 1019\n", " 14 0.048951 0.035354 0.041056 792\n", " 15 0.033708 0.023659 0.027804 634\n", " 16 0.042857 0.028090 0.033937 534\n", " 17 0.003968 0.002053 0.002706 487\n", " 18 0.040000 0.023041 0.029240 434\n", " 19 0.621456 0.555772 0.586782 8203\n", " 20 0.310580 0.411021 0.353810 1107\n", "\n", "avg / total 0.368050 0.361798 0.360564 17355\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 1, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 19 0.987366 0.996567 0.991945 16311\n", " 20 0.937220 0.800766 0.863636 1044\n", "\n", "avg / total 0.984349 0.984788 0.984226 17355\n", "\n", "Classification report for turbine 1, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 664\n", " 11 0.000000 0.000000 0.000000 419\n", " 12 0.000000 0.000000 0.000000 360\n", " 13 0.000000 0.000000 0.000000 360\n", " 14 0.000000 0.000000 0.000000 259\n", " 15 0.000000 0.000000 0.000000 216\n", " 16 0.000000 0.000000 0.000000 216\n", " 17 0.000000 0.000000 0.000000 208\n", " 18 0.000000 0.000000 0.000000 180\n", " 19 0.866287 0.995937 0.926599 13290\n", " 20 0.471098 0.826712 0.600184 1183\n", "\n", "avg / total 0.695492 0.819015 0.750476 17355\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 1, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.021941 0.891892 0.042829 37\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 15\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.868798 0.768591 0.815628 9615\n", " 20 0.898305 0.865364 0.881527 7472\n", "\n", "avg / total 0.868133 0.800288 0.831496 17355\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 1, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.508264 0.217314 0.304455 566\n", " 11 0.000000 0.000000 0.000000 252\n", " 12 0.019231 0.003968 0.006579 252\n", " 13 0.000000 0.000000 0.000000 252\n", " 14 0.121212 0.015873 0.028070 252\n", " 15 0.000000 0.000000 0.000000 252\n", " 16 0.000000 0.000000 0.000000 252\n", " 17 0.090909 0.011905 0.021053 252\n", " 18 0.000000 0.000000 0.000000 252\n", " 19 0.849598 0.976372 0.908584 11681\n", " 20 0.832791 0.910091 0.869726 3092\n", "\n", "avg / total 0.740139 0.826851 0.777224 17355\n", "\n", "Classification report for turbine 1, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.537092 0.234153 0.326126 773\n", " 11 0.106383 0.006859 0.012887 729\n", " 12 0.000000 0.000000 0.000000 482\n", " 13 0.040000 0.002857 0.005333 350\n", " 14 0.000000 0.000000 0.000000 303\n", " 15 0.000000 0.000000 0.000000 250\n", " 16 0.000000 0.000000 0.000000 216\n", " 17 0.000000 0.000000 0.000000 216\n", " 18 0.011765 0.004630 0.006645 216\n", " 19 0.820236 0.973855 0.890469 11704\n", " 20 0.682997 0.896030 0.775143 2116\n", "\n", "avg / total 0.665775 0.776837 0.710288 17355\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 1, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.986944 0.996444 0.991671 16311\n", " 20 0.934611 0.794061 0.858622 1044\n", "\n", "avg / total 0.983796 0.984270 0.983668 17355\n", "\n", "Classification report for turbine 1, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.982460 0.995953 0.989160 15072\n", " 20 0.970617 0.882611 0.924524 2283\n", "\n", "avg / total 0.980902 0.981043 0.980657 17355\n", "\n", "Classification report for turbine 1, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.873295 0.936719 0.903896 9845\n", " 20 0.908315 0.821838 0.862915 7510\n", "\n", "avg / total 0.888449 0.887007 0.886162 17355\n", "\n", "Classification report for turbine 1, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 22\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.975860 0.993501 0.984602 13387\n", " 20 0.945250 0.962821 0.953954 3658\n", "\n", "avg / total 0.951977 0.969288 0.960555 17355\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 1, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 57\n", " 11 0.000000 0.000000 0.000000 132\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.916737 0.993689 0.953663 13152\n", " 20 0.947248 0.892879 0.919261 3258\n", "\n", "avg / total 0.872547 0.920657 0.895277 17355\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 1, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 32\n", " 11 0.000000 0.000000 0.000000 180\n", " 12 0.000000 0.000000 0.000000 216\n", " 13 0.000000 0.000000 0.000000 216\n", " 14 0.000000 0.000000 0.000000 216\n", " 15 0.000000 0.000000 0.000000 216\n", " 16 0.000000 0.000000 0.000000 216\n", " 17 0.000000 0.000000 0.000000 216\n", " 18 0.000000 0.000000 0.000000 216\n", " 19 0.885872 0.996720 0.938033 14633\n", " 20 0.909091 0.811623 0.857597 998\n", "\n", "avg / total 0.799207 0.887064 0.840225 17355\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 1, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.066667 0.083333 0.074074 12\n", " 11 0.017094 0.027778 0.021164 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.030000 0.041667 0.034884 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.009901 0.013889 0.011561 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.948806 0.943857 0.946325 14570\n", " 20 0.937885 0.831589 0.881544 2197\n", "\n", "avg / total 0.915560 0.898070 0.906394 17355\n", "\n", "Classification report for turbine 1, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 20\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.166667 0.027778 0.047619 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.034483 0.009259 0.014599 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.732357 0.729420 0.730885 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12556\n", " 20 0.937984 0.935395 0.936688 3622\n", "\n", "avg / total 0.857438 0.893518 0.874892 17355\n", "\n", "Classification report for turbine 1, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 7\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.047619 0.027778 0.035088 36\n", " 19 0.962735 0.970672 0.966687 13707\n", " 20 0.979424 0.922756 0.950246 3353\n", "\n", "avg / total 0.949694 0.944973 0.947152 17355\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 1, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.985560 0.995892 0.990699 16311\n", " 20 0.923253 0.772031 0.840897 1044\n", "\n", "avg 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precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.989057 0.991752 0.990403 13579\n", " 20 0.980769 0.958951 0.969738 3776\n", "\n", "avg / total 0.987254 0.984615 0.985906 17355\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 1, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.983366 0.992357 0.987841 14000\n", " 20 0.971760 0.923100 0.946805 3355\n", "\n", "avg / total 0.981123 0.978969 0.979908 17355\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 1, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.985072 0.995218 0.990119 16311\n", " 20 0.910959 0.764368 0.831250 1044\n", "\n", "avg / total 0.980614 0.981331 0.980562 17355\n", "\n", "Classification report for turbine 1, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.976725 0.996749 0.986635 15072\n", " 20 0.975177 0.843189 0.904393 2283\n", "\n", "avg / total 0.976521 0.976549 0.975816 17355\n", "\n", "Classification report for turbine 1, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 8763\n", " 19 0.731371 0.994994 0.843054 7191\n", " 20 0.146857 0.793719 0.247855 1401\n", "\n", "avg / total 0.314897 0.476347 0.369326 17355\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 1, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 10 0.092683 0.060317 0.073077 315\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.962261 0.987220 0.974581 13224\n", " 20 0.842869 0.932099 0.885241 3240\n", "\n", "avg / total 0.892252 0.927341 0.909194 17355\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 1, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 4\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.963334 0.982720 0.972930 13715\n", " 20 0.973935 0.915173 0.943640 3348\n", "\n", "avg / total 0.949171 0.953155 0.950910 17355\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 2, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 4\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.953964 0.983172 0.968348 16461\n", " 20 0.971255 0.834065 0.897447 3646\n", "\n", "avg / total 0.943399 0.942448 0.941814 20399\n", "\n", "Classification report for turbine 2, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 57\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 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0.000000 144\n", " 15 0.000000 0.000000 0.000000 119\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.912521 0.980214 0.945157 15718\n", " 20 0.903886 0.878098 0.890805 3470\n", "\n", "avg / total 0.856880 0.904652 0.879801 20399\n", "\n", "Classification report for turbine 2, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 84\n", " 11 0.000000 0.000000 0.000000 40\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.086957 0.055556 0.067797 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.955387 0.985793 0.970352 16119\n", " 20 0.958345 0.889857 0.922832 3904\n", "\n", "avg / total 0.938497 0.949360 0.943491 20399\n", "\n", "Classification report for turbine 2, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.057143 0.250000 0.093023 8\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.962780 0.986117 0.974309 13614\n", " 20 0.972029 0.947912 0.959819 6489\n", "\n", "avg / total 0.951774 0.959753 0.955598 20399\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 2, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 5\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.961950 0.995140 0.978263 16462\n", " 20 0.974770 0.901207 0.936546 3644\n", "\n", "avg / total 0.950423 0.964067 0.956760 20399\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 2, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 279\n", " 11 0.000000 0.000000 0.000000 276\n", " 12 0.000000 0.000000 0.000000 252\n", " 13 0.000000 0.000000 0.000000 236\n", " 14 0.000000 0.000000 0.000000 216\n", " 15 0.000000 0.000000 0.000000 216\n", " 16 0.000000 0.000000 0.000000 216\n", " 17 0.000000 0.000000 0.000000 216\n", " 18 0.000000 0.000000 0.000000 216\n", " 19 0.881817 0.991387 0.933398 16603\n", " 20 0.683384 0.676031 0.679687 1673\n", "\n", "avg / total 0.773769 0.862346 0.815448 20399\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 2, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.037815 0.450000 0.069767 20\n", " 11 0.019841 0.138889 0.034722 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.984724 0.960429 0.972425 16780\n", " 20 0.850963 0.813953 0.832047 3311\n", "\n", "avg / total 0.948217 0.922839 0.935087 20399\n", "\n", "Classification report for turbine 2, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.967091 0.954758 0.960885 16467\n", " 20 0.964521 0.857325 0.907769 3932\n", "\n", "avg / total 0.966596 0.935977 0.950647 20399\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 2, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.005128 0.011628 0.007117 86\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.949934 0.970287 0.960003 13395\n", " 20 0.940849 0.932986 0.936901 6342\n", "\n", "avg / total 0.916303 0.927251 0.921696 20399\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 2, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.979653 0.994864 0.987200 16745\n", " 20 0.974661 0.905309 0.938706 3654\n", "\n", "avg / total 0.978759 0.978822 0.978513 20399\n", "\n", "Classification report for turbine 2, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.967778 0.992540 0.980003 18096\n", " 20 0.926630 0.740339 0.823075 2303\n", "\n", "avg / total 0.963133 0.964067 0.962286 20399\n", "\n", "Classification report for turbine 2, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.989173 0.985401 0.987284 16782\n", " 20 0.933442 0.949959 0.941628 3617\n", "\n", "avg / total 0.979291 0.979117 0.979188 20399\n", "\n", "Classification report for turbine 2, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.970588 0.993988 0.982149 16467\n", " 20 0.971994 0.873856 0.920316 3932\n", "\n", "avg / total 0.970859 0.970832 0.970230 20399\n", "\n", "Classification report for turbine 2, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.985007 0.988284 0.986643 13827\n", " 20 0.975176 0.968351 0.971751 6572\n", "\n", "avg / total 0.981840 0.981862 0.981845 20399\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 2, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.233766 0.835714 0.365340 280\n", " 11 0.007042 0.050314 0.012355 159\n", " 12 0.001842 0.006944 0.002911 144\n", " 13 0.009296 0.048611 0.015608 144\n", " 14 0.006303 0.020833 0.009677 144\n", " 15 0.003247 0.006944 0.004425 144\n", " 16 0.000000 0.000000 0.000000 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.004484 0.006944 0.005450 144\n", " 19 0.905993 0.807616 0.853981 15573\n", " 20 0.951189 0.449837 0.610810 3379\n", "\n", "avg / total 0.852655 0.703564 0.758503 20399\n", "\n", "Classification report for turbine 2, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.019569 0.103627 0.032922 193\n", " 11 0.008621 0.002525 0.003906 396\n", " 12 0.013699 0.005051 0.007380 396\n", " 13 0.000000 0.000000 0.000000 396\n", " 14 0.004425 0.002667 0.003328 375\n", " 15 0.078431 0.012346 0.021333 324\n", " 16 0.000000 0.000000 0.000000 296\n", " 17 0.017241 0.003472 0.005780 288\n", " 18 0.000000 0.000000 0.000000 288\n", " 19 0.834911 0.924276 0.877324 15649\n", " 20 0.752137 0.489433 0.592992 1798\n", "\n", "avg / total 0.708982 0.753615 0.726314 20399\n", "\n", "Classification report for turbine 2, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.636620 0.361022 0.460754 626\n", " 11 0.028846 0.021544 0.024666 557\n", " 12 0.056452 0.014862 0.023529 471\n", " 13 0.008475 0.002188 0.003478 457\n", " 14 0.026316 0.017812 0.021244 393\n", " 15 0.000000 0.000000 0.000000 360\n", " 16 0.000000 0.000000 0.000000 329\n", " 17 0.013333 0.003257 0.005236 307\n", " 18 0.084112 0.031250 0.045570 288\n", " 19 0.823328 0.923700 0.870631 14076\n", " 20 0.687023 0.781065 0.731032 2535\n", "\n", "avg / total 0.677214 0.747341 0.708176 20399\n", "\n", "Classification report for turbine 2, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.177137 0.421569 0.249456 408\n", " 11 0.008929 0.002519 0.003929 397\n", " 12 0.011173 0.005051 0.006957 396\n", " 13 0.000000 0.000000 0.000000 396\n", " 14 0.024793 0.007732 0.011788 388\n", " 15 0.024691 0.006645 0.010471 301\n", " 16 0.012500 0.003968 0.006024 252\n", " 17 0.000000 0.000000 0.000000 252\n", " 18 0.000000 0.000000 0.000000 229\n", " 19 0.825064 0.915892 0.868109 14089\n", " 20 0.809619 0.736554 0.771360 3291\n", "\n", "avg / total 0.705389 0.760282 0.729676 20399\n", "\n", "Classification report for turbine 2, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.045372 0.471698 0.082781 53\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.960579 0.947512 0.954001 13527\n", " 20 0.947444 0.840301 0.890662 6243\n", "\n", "avg / total 0.927058 0.886710 0.905415 20399\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 2, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 10 0.909091 0.004078 0.008120 2452\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.935681 0.990741 0.962424 16093\n", " 20 0.274947 0.705008 0.395609 1278\n", "\n", "avg / total 0.864669 0.826266 0.785028 20399\n", "\n", "Classification 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0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.986522 0.976999 0.981738 16782\n", " 20 0.938876 0.789881 0.857958 3617\n", "\n", "avg / total 0.978074 0.943821 0.959790 20399\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 2, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 10 0.005618 0.038627 0.009809 233\n", " 11 0.000000 0.000000 0.000000 86\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.944895 0.952089 0.948478 16155\n", " 20 0.819974 0.559193 0.664929 3421\n", "\n", "avg / total 0.885887 0.848228 0.862771 20399\n", "\n", "Classification report for turbine 2, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.979741 0.972301 0.976006 13827\n", " 20 0.974367 0.937005 0.955321 6572\n", "\n", "avg / total 0.978009 0.960929 0.969342 20399\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program 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0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 19 0.976342 0.987922 0.982098 13827\n", " 20 0.975165 0.944005 0.959332 6572\n", "\n", "avg / total 0.975963 0.973773 0.974763 20399\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 2, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 246\n", " 11 0.000000 0.000000 0.000000 155\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 67\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 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0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.980254 0.973245 0.976737 16782\n", " 20 0.916616 0.838817 0.875992 3617\n", "\n", "avg / total 0.968971 0.949409 0.958874 20399\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 2, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.020325 0.192308 0.036765 26\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.947889 0.988269 0.967658 16197\n", " 20 0.868571 0.760000 0.810667 3600\n", "\n", "avg / total 0.905944 0.919065 0.911442 20399\n", "\n", "Classification report for turbine 2, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 16\n", " 11 0.000000 0.000000 0.000000 144\n", " 12 0.263158 0.034722 0.061350 144\n", " 13 0.000000 0.000000 0.000000 144\n", " 14 0.000000 0.000000 0.000000 144\n", " 15 0.000000 0.000000 0.000000 144\n", " 16 0.000000 0.000000 0.000000 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.006536 0.006944 0.006734 144\n", " 19 0.910408 0.969014 0.938797 12909\n", " 20 0.942196 0.946220 0.944203 6322\n", "\n", "avg / total 0.870035 0.906760 0.887200 20399\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 2, turbine category 9.0\n", " 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'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 2, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.968813 0.980217 0.974482 18096\n", " 20 0.931892 0.748589 0.830243 2303\n", "\n", "avg / total 0.964645 0.954066 0.958197 20399\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 2, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.666667 0.285714 0.400000 7\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.970744 0.977985 0.974351 16489\n", " 20 0.930790 0.944952 0.937817 3615\n", "\n", "avg / total 0.949854 0.958086 0.953924 20399\n", "\n", "Classification report for turbine 2, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.036364 0.025682 0.030103 623\n", " 11 0.122449 0.015190 0.027027 395\n", " 12 0.000000 0.000000 0.000000 305\n", " 13 0.000000 0.000000 0.000000 222\n", " 14 0.000000 0.000000 0.000000 180\n", " 15 0.000000 0.000000 0.000000 180\n", " 16 0.000000 0.000000 0.000000 180\n", " 17 0.000000 0.000000 0.000000 180\n", " 18 0.000000 0.000000 0.000000 180\n", " 19 0.876901 0.956769 0.915096 14943\n", " 20 0.728357 0.852209 0.785430 3011\n", "\n", "avg / total 0.753353 0.827737 0.787717 20399\n", "\n", "Classification report for turbine 2, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.182390 0.034898 0.058586 831\n", " 11 0.000000 0.000000 0.000000 432\n", " 12 0.000000 0.000000 0.000000 385\n", " 13 0.000000 0.000000 0.000000 324\n", " 14 0.000000 0.000000 0.000000 314\n", " 15 0.000000 0.000000 0.000000 288\n", " 16 0.000000 0.000000 0.000000 288\n", " 17 0.000000 0.000000 0.000000 288\n", " 18 0.000000 0.000000 0.000000 288\n", " 19 0.814175 0.980611 0.889676 11398\n", " 20 0.828634 0.956139 0.887832 5563\n", "\n", "avg / total 0.688329 0.810089 0.741616 20399\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 2, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 19 0.976359 0.993968 0.985085 16745\n", " 20 0.969869 0.889710 0.928062 3654\n", "\n", "avg / total 0.975197 0.975293 0.974871 20399\n", "\n", "Classification report for turbine 2, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 986\n", " 11 0.000000 0.000000 0.000000 289\n", " 12 0.000000 0.000000 0.000000 260\n", " 13 0.000000 0.000000 0.000000 217\n", " 14 0.000000 0.000000 0.000000 180\n", " 15 0.000000 0.000000 0.000000 180\n", " 16 0.000000 0.000000 0.000000 180\n", " 17 0.000000 0.000000 0.000000 180\n", " 18 0.000000 0.000000 0.000000 158\n", " 19 0.883094 0.992703 0.934696 16307\n", " 20 0.617021 0.872777 0.722946 1462\n", "\n", "avg / total 0.750169 0.856120 0.799011 20399\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 2, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.172285 0.145110 0.157534 317\n", " 11 0.000000 0.000000 0.000000 112\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.032258 0.009259 0.014388 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.925370 0.968361 0.946378 15993\n", " 20 0.809267 0.791680 0.800377 3221\n", "\n", "avg / total 0.856130 0.886514 0.870872 20399\n", "\n", "Classification report for turbine 2, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.007005 0.012461 0.008969 321\n", " 11 0.000000 0.000000 0.000000 144\n", " 12 0.000000 0.000000 0.000000 144\n", " 13 0.000000 0.000000 0.000000 144\n", " 14 0.000000 0.000000 0.000000 144\n", " 15 0.000000 0.000000 0.000000 128\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.908360 0.947620 0.927575 15502\n", " 20 0.859088 0.817926 0.838002 3548\n", "\n", "avg / total 0.839830 0.862591 0.850795 20399\n", "\n", "Classification report for turbine 2, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.566596 0.061808 0.111458 4336\n", " 11 0.008772 0.001555 0.002642 643\n", " 12 0.000000 0.000000 0.000000 540\n", " 13 0.000000 0.000000 0.000000 502\n", " 14 0.065217 0.006944 0.012552 432\n", " 15 0.019608 0.002315 0.004141 432\n", " 16 0.000000 0.000000 0.000000 432\n", " 17 0.043478 0.002463 0.004662 406\n", " 18 0.037037 0.002653 0.004950 377\n", " 19 0.754716 0.962184 0.845915 10604\n", " 20 0.239835 0.856047 0.374693 1695\n", "\n", "avg / total 0.536310 0.584784 0.495178 20399\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 2, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.979473 0.994506 0.986932 16745\n", " 20 0.972917 0.904488 0.937456 3654\n", "\n", "avg / total 0.978299 0.978381 0.978070 20399\n", "\n", "Classification report for turbine 2, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.951776 0.993590 0.972233 18096\n", " 20 0.923077 0.604429 0.730517 2303\n", "\n", "avg / total 0.948536 0.949654 0.944944 20399\n", "\n", "Classification report for turbine 2, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.990333 0.982839 0.986572 16782\n", " 20 0.923077 0.955488 0.939003 3617\n", "\n", "avg / total 0.978408 0.977989 0.978137 20399\n", "\n", "Classification report for turbine 2, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 16\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.975150 0.994651 0.984804 16452\n", " 20 0.896352 0.890200 0.893265 3643\n", "\n", "avg / total 0.946546 0.961175 0.953780 20399\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 2, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.982353 0.978303 0.980324 13827\n", " 20 0.974292 0.963025 0.968626 6572\n", "\n", "avg / total 0.979756 0.973381 0.976555 20399\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 2, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 53\n", " 11 0.333333 0.003472 0.006873 288\n", " 12 0.000000 0.000000 0.000000 288\n", " 13 0.000000 0.000000 0.000000 288\n", " 14 0.000000 0.000000 0.000000 288\n", " 15 0.033333 0.007353 0.012048 272\n", " 16 0.000000 0.000000 0.000000 252\n", " 17 0.000000 0.000000 0.000000 252\n", " 18 0.000000 0.000000 0.000000 252\n", " 19 0.857583 0.985420 0.917068 14678\n", " 20 0.935312 0.903670 0.919218 3488\n", "\n", "avg / total 0.782148 0.863719 0.817306 20399\n", "\n", "Classification report for turbine 2, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.133333 0.080000 0.100000 25\n", " 11 0.160494 0.090278 0.115556 144\n", " 12 0.012821 0.013889 0.013333 144\n", " 13 0.020000 0.006944 0.010309 144\n", " 14 0.000000 0.000000 0.000000 144\n", " 15 0.008734 0.013889 0.010724 144\n", " 16 0.001855 0.006944 0.002928 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.007009 0.020833 0.010490 144\n", " 19 0.908520 0.900723 0.904604 17013\n", " 20 0.888179 0.629244 0.736619 2209\n", "\n", "avg / total 0.855549 0.820530 0.835494 20399\n", "\n", "Classification report for turbine 2, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.039604 0.210526 0.066667 19\n", " 11 0.027972 0.037037 0.031873 108\n", " 12 0.021277 0.018519 0.019802 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.016949 0.009259 0.011976 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.941235 0.954055 0.947601 15932\n", " 20 0.913213 0.916016 0.914612 3584\n", "\n", "avg / total 0.895956 0.906613 0.901186 20399\n", "\n", "Classification report for turbine 2, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 18\n", " 11 0.029046 0.064815 0.040115 108\n", " 12 0.028571 0.018519 0.022472 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.021739 0.009259 0.012987 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.020408 0.009259 0.012739 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.927209 0.962506 0.944528 15656\n", " 20 0.936869 0.841751 0.886767 3861\n", "\n", "avg / total 0.889476 0.898573 0.893224 20399\n", "\n", "Classification report for turbine 2, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.052632 0.083333 0.064516 12\n", " 11 0.097561 0.055556 0.070796 72\n", " 12 0.029412 0.013889 0.018868 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.062500 0.027778 0.038462 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.947257 0.974230 0.960554 13310\n", " 20 0.967167 0.951546 0.959293 6501\n", "\n", "avg / total 0.926997 0.939311 0.932954 20399\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 2, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.980054 0.994745 0.987345 16745\n", " 20 0.974140 0.907225 0.939493 3654\n", "\n", "avg / total 0.978995 0.979068 0.978773 20399\n", "\n", "Classification report for turbine 2, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.978861 0.992871 0.985817 18096\n", " 20 0.936888 0.831524 0.881067 2303\n", "\n", "avg / total 0.974123 0.974656 0.973991 20399\n", "\n", "Classification report for turbine 2, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.989095 0.983613 0.986346 16782\n", " 20 0.925876 0.949682 0.937628 3617\n", "\n", "avg / total 0.977885 0.977597 0.977708 20399\n", "\n", "Classification report for turbine 2, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.973752 0.993502 0.983528 16467\n", " 20 0.970261 0.887843 0.927224 3932\n", "\n", "avg / total 0.973079 0.973136 0.972675 20399\n", "\n", "Classification report for turbine 2, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.986636 0.987778 0.987206 13827\n", " 20 0.974222 0.971850 0.973035 6572\n", "\n", "avg / total 0.982636 0.982646 0.982641 20399\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 2, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.980158 0.994148 0.987103 16745\n", " 20 0.971303 0.907772 0.938464 3654\n", "\n", "avg / total 0.978572 0.978675 0.978390 20399\n", "\n", "Classification report for turbine 2, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.974905 0.993977 0.984348 18096\n", " 20 0.944074 0.798958 0.865475 2303\n", "\n", "avg / total 0.971424 0.971959 0.970928 20399\n", "\n", "Classification report for turbine 2, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.991882 0.982839 0.987339 16782\n", " 20 0.923607 0.962676 0.942737 3617\n", "\n", "avg / total 0.979776 0.979264 0.979431 20399\n", "\n", "Classification report for turbine 2, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 23\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.959418 0.993757 0.976285 16177\n", " 20 0.966511 0.900281 0.932221 3911\n", "\n", "avg / total 0.946150 0.960684 0.952953 20399\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 2, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 56\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 99\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.333333 0.013889 0.026667 72\n", " 19 0.945255 0.986062 0.965227 13273\n", " 20 0.949670 0.967787 0.958643 6395\n", "\n", "avg / total 0.913942 0.945046 0.928668 20399\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 3, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 62\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.000000 0.000000 0.000000 97\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.947256 0.983151 0.964870 16678\n", " 20 0.920739 0.934842 0.927737 4374\n", "\n", "avg / total 0.911482 0.941842 0.926395 21751\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 3, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 41\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.090909 0.027778 0.042553 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.974433 0.974327 0.974380 18385\n", " 20 0.891086 0.934804 0.912422 3037\n", "\n", "avg / total 0.948207 0.954117 0.951061 21751\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 3, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.984449 0.971257 0.977809 15969\n", " 20 0.942128 0.957281 0.949644 5782\n", "\n", "avg / total 0.973199 0.967542 0.970322 21751\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 3, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 51\n", " 11 0.200000 0.013889 0.025974 72\n", " 12 0.285714 0.027778 0.050633 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.967294 0.988822 0.977940 19950\n", " 20 0.805810 0.897785 0.849315 1174\n", "\n", "avg / total 0.932303 0.955542 0.943061 21751\n", "\n", "Classification report for turbine 3, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.990509 0.992852 0.991679 19446\n", " 20 0.950202 0.918872 0.934274 2305\n", "\n", "avg / total 0.986238 0.985012 0.985596 21751\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall 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"name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 3, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.982696 0.981219 0.981957 17305\n", " 20 0.927326 0.932749 0.930029 4446\n", "\n", "avg / total 0.971378 0.971312 0.971343 21751\n", "\n", "Classification report for turbine 3, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.992054 0.983284 0.987650 18665\n", " 20 0.904030 0.952366 0.927568 3086\n", "\n", "avg / total 0.979565 0.978898 0.979125 21751\n", "\n", "Classification report for turbine 3, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.987275 0.981401 0.984329 15969\n", " 20 0.949464 0.965064 0.957200 5782\n", "\n", "avg / total 0.977224 0.977059 0.977118 21751\n", "\n", "Classification report for turbine 3, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.995986 0.992149 0.994064 20507\n", " 20 0.878307 0.934084 0.905337 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}, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 3, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 7\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.962601 0.965728 0.964162 15698\n", " 20 0.934860 0.907259 0.920853 5758\n", "\n", "avg / total 0.942202 0.937152 0.939621 21751\n", "\n", "Classification report for 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" 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.976192 0.959607 0.967828 17305\n", " 20 0.921923 0.871120 0.895802 4446\n", "\n", "avg / total 0.965099 0.941520 0.953106 21751\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 3, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 49\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 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turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 14\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.984966 0.993119 0.989026 19329\n", " 20 0.874944 0.920755 0.897265 2120\n", "\n", "avg / total 0.960567 0.972277 0.966350 21751\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 3, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 92\n", " 11 0.022599 0.006601 0.010217 606\n", " 12 0.002169 0.001852 0.001998 540\n", " 13 0.002801 0.001866 0.002240 536\n", " 14 0.019608 0.004357 0.007130 459\n", " 15 0.000000 0.000000 0.000000 405\n", " 16 0.080000 0.005051 0.009501 396\n", " 17 0.066667 0.002597 0.005000 385\n", " 18 0.000000 0.000000 0.000000 319\n", " 19 0.829670 0.917157 0.871223 14775\n", " 20 0.676492 0.871834 0.761841 3238\n", "\n", "avg / total 0.668087 0.753299 0.706018 21751\n", "\n", "Classification report for turbine 3, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.014493 0.250000 0.027397 4\n", " 11 0.061538 0.111111 0.079208 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.980684 0.972588 0.976619 18532\n", " 20 0.837302 0.865050 0.850949 2927\n", "\n", "avg / total 0.948329 0.945290 0.946734 21751\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 3, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.040541 0.053571 0.046154 56\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 100\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.936372 0.969836 0.952810 15250\n", " 20 0.930212 0.932322 0.931266 5733\n", "\n", "avg / total 0.901791 0.925842 0.913608 21751\n", "\n", "Classification report for turbine 3, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 23\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.096774 0.041667 0.058252 72\n", " 13 0.000000 0.000000 0.000000 87\n", " 14 0.050000 0.009259 0.015625 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.958008 0.982321 0.970012 19741\n", " 20 0.808415 0.884868 0.844916 1216\n", "\n", "avg / total 0.915242 0.941198 0.927880 21751\n", "\n", "Classification report for turbine 3, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.076923 0.028777 0.041885 139\n", " 11 0.034483 0.009259 0.014599 216\n", " 12 0.000000 0.000000 0.000000 216\n", " 13 0.000000 0.000000 0.000000 201\n", " 14 0.036232 0.031250 0.033557 160\n", " 15 0.038462 0.020833 0.027027 144\n", " 16 0.000000 0.000000 0.000000 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.031250 0.013889 0.019231 144\n", " 19 0.924929 0.968866 0.946388 18083\n", " 20 0.884944 0.911574 0.898062 2160\n", "\n", "avg / total 0.858395 0.896740 0.876941 21751\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 3, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 142\n", " 11 0.015873 0.009259 0.011696 216\n", " 12 0.015873 0.009259 0.011696 216\n", " 13 0.000000 0.000000 0.000000 216\n", " 14 0.000000 0.000000 0.000000 216\n", " 15 0.000000 0.000000 0.000000 216\n", " 16 0.000000 0.000000 0.000000 200\n", " 17 0.000000 0.000000 0.000000 180\n", " 18 0.048780 0.011111 0.018100 180\n", " 19 0.896669 0.930494 0.913269 15826\n", " 20 0.854220 0.886797 0.870204 4143\n", "\n", "avg / total 0.815841 0.846214 0.830626 21751\n", "\n", "Classification report for turbine 3, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 5\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.977732 0.945975 0.961591 18473\n", " 20 0.866777 0.878392 0.872546 2985\n", "\n", "avg / total 0.949334 0.923958 0.936418 21751\n", "\n", "Classification report for turbine 3, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.157895 0.046154 0.071429 195\n", " 11 0.000000 0.000000 0.000000 153\n", " 12 0.000000 0.000000 0.000000 103\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.947358 0.969297 0.958202 15373\n", " 20 0.906349 0.935214 0.920555 5495\n", "\n", "avg / total 0.899955 0.921751 0.910433 21751\n", "\n", "Classification report for turbine 3, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 14\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.955486 0.982125 0.968622 19692\n", " 20 0.801521 0.892464 0.844551 1181\n", "\n", "avg / total 0.908557 0.937612 0.922786 21751\n", "\n", "Classification report for turbine 3, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.063830 0.028037 0.038961 107\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.967112 0.986934 0.976922 18980\n", " 20 0.859553 0.902778 0.880635 2088\n", "\n", "avg / total 0.926733 0.948002 0.937195 21751\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 3, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.720752 0.825688 0.769660 2507\n", " 11 0.115654 0.380145 0.177351 1652\n", " 12 0.063743 0.135813 0.086764 1156\n", " 13 0.045773 0.109961 0.064639 773\n", " 14 0.011082 0.036778 0.017032 571\n", " 15 0.015168 0.034739 0.021116 403\n", " 16 0.025751 0.037975 0.030691 316\n", " 17 0.032258 0.040984 0.036101 244\n", " 18 0.006275 0.037037 0.010731 216\n", " 19 0.699111 0.227694 0.343510 12082\n", " 20 0.430769 0.076461 0.129870 1831\n", "\n", "avg / total 0.522838 0.271068 0.312626 21751\n", "\n", "Classification report for turbine 3, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.038647 0.615385 0.072727 78\n", " 11 0.005495 0.006944 0.006135 288\n", " 12 0.000000 0.000000 0.000000 288\n", " 13 0.014862 0.025830 0.018868 271\n", " 14 0.003534 0.003968 0.003738 252\n", " 15 0.006329 0.003968 0.004878 252\n", " 16 0.005650 0.003968 0.004662 252\n", " 17 0.068182 0.023810 0.035294 252\n", " 18 0.000000 0.000000 0.000000 252\n", " 19 0.897091 0.892965 0.895023 16957\n", " 20 0.779762 0.401686 0.530230 2609\n", "\n", "avg / total 0.794266 0.747368 0.762497 21751\n", "\n", "Classification report for turbine 3, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.000672 0.111111 0.001337 9\n", " 11 0.017241 0.055556 0.026316 72\n", " 12 0.007519 0.027778 0.011834 72\n", " 13 0.014925 0.027778 0.019417 72\n", " 14 0.011765 0.013889 0.012739 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.945613 0.931066 0.938283 15406\n", " 20 0.924926 0.654514 0.766572 5760\n", "\n", "avg / total 0.914873 0.833249 0.867809 21751\n", "\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 3, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.723810 0.590674 0.650499 386\n", " 11 0.000000 0.000000 0.000000 144\n", " 12 0.000000 0.000000 0.000000 144\n", " 13 0.000000 0.000000 0.000000 144\n", " 14 0.000000 0.000000 0.000000 144\n", " 15 0.000000 0.000000 0.000000 144\n", " 16 0.000000 0.000000 0.000000 144\n", " 17 0.000000 0.000000 0.000000 143\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.938707 0.966085 0.952199 19372\n", " 20 0.650743 0.698178 0.673626 878\n", "\n", "avg / total 0.875149 0.899085 0.886789 21751\n", "\n", "Classification report for turbine 3, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 4\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.976991 0.976889 0.976940 19168\n", " 20 0.921305 0.628546 0.747276 2291\n", "\n", "avg / total 0.958009 0.927084 0.939634 21751\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 3, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 19 0.981641 0.982548 0.982094 17305\n", " 20 0.931828 0.928475 0.930149 4446\n", "\n", "avg / total 0.971459 0.971496 0.971476 21751\n", "\n", "Classification report for turbine 3, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 1496\n", " 11 0.000000 0.000000 0.000000 613\n", " 12 0.000000 0.000000 0.000000 424\n", " 13 0.000000 0.000000 0.000000 381\n", " 14 0.000000 0.000000 0.000000 347\n", " 15 0.000000 0.000000 0.000000 324\n", " 16 0.000000 0.000000 0.000000 238\n", " 17 0.000000 0.000000 0.000000 216\n", " 18 0.000000 0.000000 0.000000 200\n", " 19 0.844529 0.982152 0.908156 15912\n", " 20 0.452865 0.918750 0.606686 1600\n", "\n", "avg / total 0.651130 0.786079 0.708991 21751\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 3, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.022059 0.004505 0.007481 666\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.964699 0.959087 0.961885 15643\n", " 20 0.797841 0.941636 0.863795 4866\n", "\n", "avg / total 0.872961 0.900556 0.885245 21751\n", "\n", "Classification report for turbine 3, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.032258 0.017857 0.022989 56\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 86\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.058824 0.009259 0.016000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.958133 0.981347 0.969601 19729\n", " 20 0.818731 0.906355 0.860317 1196\n", "\n", "avg / total 0.914458 0.940049 0.926910 21751\n", "\n", "Classification report for turbine 3, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 20\n", " 11 0.000000 0.000000 0.000000 144\n", " 12 0.000000 0.000000 0.000000 144\n", " 13 0.023529 0.015385 0.018605 130\n", " 14 0.005025 0.009259 0.006515 108\n", " 15 0.006757 0.009259 0.007812 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.020202 0.018519 0.019324 108\n", " 19 0.941610 0.959868 0.950651 18514\n", " 20 0.927586 0.833555 0.878060 2259\n", "\n", "avg / total 0.898115 0.903866 0.900646 21751\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 3, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.982394 0.983473 0.982933 17305\n", " 20 0.935396 0.931399 0.933393 4446\n", "\n", "avg / total 0.972788 0.972829 0.972807 21751\n", "\n", "Classification report for turbine 3, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.992377 0.983391 0.987864 18665\n", " 20 0.904762 0.954310 0.928876 3086\n", "\n", "avg / total 0.979946 0.979265 0.979494 21751\n", "\n", "Classification report for turbine 3, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 64\n", " 11 0.000000 0.000000 0.000000 37\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.976812 0.979961 0.978384 15819\n", " 20 0.913790 0.963255 0.937871 5579\n", "\n", "avg / total 0.944794 0.959772 0.952114 21751\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 3, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 19 0.995836 0.991174 0.993499 20507\n", " 20 0.869467 0.931672 0.899496 1244\n", "\n", "avg / total 0.988608 0.987771 0.988123 21751\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 3, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 19 0.991234 0.994343 0.992786 19446\n", " 20 0.953956 0.925813 0.939674 2305\n", "\n", "avg / total 0.987284 0.987081 0.987158 21751\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 3, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.250000 0.074074 0.114286 54\n", " 11 0.030303 0.003086 0.005602 324\n", " 12 0.000000 0.000000 0.000000 324\n", " 13 0.000000 0.000000 0.000000 324\n", " 14 0.000000 0.000000 0.000000 324\n", " 15 0.000000 0.000000 0.000000 324\n", " 16 0.000000 0.000000 0.000000 324\n", " 17 0.000000 0.000000 0.000000 324\n", " 18 0.000000 0.000000 0.000000 287\n", " 19 0.861498 0.973936 0.914273 15232\n", " 20 0.819812 0.912276 0.863576 3910\n", "\n", "avg / total 0.751741 0.846260 0.795861 21751\n", "\n", "Classification report for turbine 3, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 6\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.025641 0.055556 0.035088 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.007653 0.083333 0.014019 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.005495 0.027778 0.009174 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.971327 0.925194 0.947700 18381\n", " 20 0.897377 0.889792 0.893568 3076\n", "\n", "avg / total 0.947805 0.907958 0.927331 21751\n", "\n", "Classification report for turbine 3, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.020000 0.150000 0.035294 20\n", " 11 0.018182 0.009259 0.012270 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.048780 0.037037 0.042105 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.926789 0.966004 0.945990 15149\n", " 20 0.929874 0.874257 0.901208 5718\n", "\n", "avg / total 0.890284 0.902993 0.896074 21751\n", "\n", "Classification report for turbine 3, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.133333 0.285714 0.181818 7\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.980793 0.977156 0.978971 20224\n", " 20 0.826707 0.894481 0.859259 1232\n", "\n", "avg / total 0.958806 0.959312 0.958972 21751\n", "\n", "Classification report for turbine 3, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 6\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.975281 0.984342 0.979790 19159\n", " 20 0.947850 0.901654 0.924175 2298\n", "\n", "avg / total 0.959200 0.962301 0.960671 21751\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 3, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.983151 0.981219 0.982184 17305\n", " 20 0.927455 0.934548 0.930988 4446\n", "\n", "avg / total 0.971767 0.971679 0.971719 21751\n", "\n", "Classification report for turbine 3, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.992501 0.985695 0.989087 18665\n", " 20 0.916926 0.954958 0.935556 3086\n", "\n", "avg / total 0.981779 0.981334 0.981492 21751\n", "\n", "Classification report for turbine 3, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.986259 0.979836 0.983037 15969\n", " 20 0.945294 0.962297 0.953720 5782\n", "\n", "avg / total 0.975369 0.975174 0.975244 21751\n", "\n", "Classification report for turbine 3, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.995594 0.991759 0.993673 20507\n", " 20 0.872260 0.927653 0.899104 1244\n", "\n", "avg / total 0.988540 0.988093 0.988264 21751\n", "\n", "Classification report for turbine 3, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.991487 0.994240 0.992862 19446\n", " 20 0.950244 0.927983 0.938982 2305\n", "\n", "avg / total 0.987117 0.987219 0.987152 21751\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 3, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.982923 0.981219 0.982071 17305\n", " 20 0.927391 0.933648 0.930509 4446\n", "\n", "avg / total 0.971572 0.971496 0.971531 21751\n", "\n", "Classification report for turbine 3, turbine category 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"\n", "avg / total 0.897465 0.934906 0.915784 21784\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 4, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.983559 0.957664 0.970438 15117\n", " 20 0.928633 0.962202 0.945120 6667\n", "\n", "avg / total 0.966749 0.959053 0.962690 21784\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 4, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 4\n", " 11 0.200000 0.055556 0.086957 36\n", " 12 1.000000 0.055556 0.105263 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.973057 0.984520 0.978755 17571\n", " 20 0.926515 0.935731 0.931100 3921\n", "\n", "avg / total 0.953619 0.962725 0.957375 21784\n", "\n" ] }, { "name": 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"\n", "avg / total 0.983714 0.983612 0.983654 21784\n", "\n", "Classification report for turbine 4, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.995889 0.986762 0.991304 20622\n", " 20 0.797927 0.927711 0.857939 1162\n", "\n", "avg / total 0.985329 0.983612 0.984190 21784\n", "\n", "Classification report for turbine 4, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.997342 0.995187 0.996263 20360\n", " 20 0.933243 0.962079 0.947441 1424\n", "\n", "avg / total 0.993152 0.993022 0.993072 21784\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 4, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 5\n", " 19 0.981910 0.905069 0.941925 17992\n", " 20 0.906891 0.910483 0.908684 3787\n", "\n", "avg / total 0.968643 0.905802 0.935930 21784\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 4, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 28\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 31\n", " 19 0.964239 0.954359 0.959274 14833\n", " 20 0.915712 0.867169 0.890780 6640\n", "\n", "avg / total 0.935682 0.914157 0.924701 21784\n", "\n", "Classification report for turbine 4, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 4\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.968977 0.982026 0.975458 17525\n", " 20 0.937722 0.929922 0.933806 3967\n", "\n", "avg / total 0.950297 0.959374 0.954797 21784\n", "\n", "Classification report for turbine 4, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 1.000000 0.000352 0.000704 2838\n", " 11 0.000000 0.000000 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"Classification report for turbine 4, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 19 0.989480 0.988590 0.989034 17791\n", " 20 0.949364 0.953168 0.951262 3993\n", "\n", "avg / total 0.982126 0.982097 0.982111 21784\n", "\n", "Classification report for turbine 4, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 228\n", " 11 0.000000 0.000000 0.000000 80\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 58\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.984497 0.990193 0.987337 20394\n", " 20 0.537736 0.886010 0.669276 772\n", "\n", "avg / total 0.940735 0.958410 0.948055 21784\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program 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"------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 4, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 72\n", " 11 0.000000 0.000000 0.000000 180\n", " 12 0.000000 0.000000 0.000000 180\n", " 13 0.000000 0.000000 0.000000 180\n", " 14 0.000000 0.000000 0.000000 173\n", " 15 0.000000 0.000000 0.000000 144\n", " 16 0.000000 0.000000 0.000000 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.932710 0.965071 0.948615 17063\n", " 20 0.803318 0.893452 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"stdout", "output_type": "stream", "text": [ "Classification report for turbine 4, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 10 0.022222 0.034483 0.027027 29\n", " 11 0.017241 0.013889 0.015385 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.953694 0.982225 0.967749 17215\n", " 20 0.935008 0.910949 0.922821 3964\n", "\n", "avg / total 0.923894 0.942068 0.932784 21784\n", "\n", "Classification report for turbine 4, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.994510 0.983804 0.989128 20622\n", " 20 0.788200 0.896730 0.838969 1162\n", "\n", "avg / total 0.983505 0.979159 0.981118 21784\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 4, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.996409 0.994843 0.995625 20360\n", " 20 0.936886 0.938202 0.937544 1424\n", "\n", "avg / total 0.992518 0.991140 0.991829 21784\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 4, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.166364 0.368952 0.229323 496\n", " 11 0.028226 0.015590 0.020086 449\n", " 12 0.000000 0.000000 0.000000 370\n", " 13 0.000000 0.000000 0.000000 307\n", " 14 0.000000 0.000000 0.000000 252\n", " 15 0.016129 0.003968 0.006369 252\n", " 16 0.000000 0.000000 0.000000 252\n", " 17 0.000000 0.000000 0.000000 252\n", " 18 0.000000 0.000000 0.000000 243\n", " 19 0.875604 0.951643 0.912041 16006\n", " 20 0.713857 0.654389 0.682830 2905\n", "\n", "avg / total 0.743110 0.795263 0.766899 21784\n", "\n", "Classification report for turbine 4, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.004710 0.176471 0.009174 17\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.959852 0.910488 0.934519 14836\n", " 20 0.882465 0.874272 0.878350 6355\n", "\n", "avg / total 0.911151 0.875275 0.892700 21784\n", "\n", "Classification report for turbine 4, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.176818 0.934375 0.297364 320\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.052632 0.010753 0.017857 93\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.958509 0.921145 0.939456 16803\n", " 20 0.907838 0.864830 0.885812 3884\n", "\n", "avg / total 0.904028 0.878489 0.887026 21784\n", "\n", "Classification report for turbine 4, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.029412 0.037736 0.033058 53\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.076923 0.055556 0.064516 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.980255 0.971866 0.976042 20331\n", " 20 0.714174 0.824640 0.765442 1112\n", "\n", "avg / total 0.951527 0.949321 0.950200 21784\n", "\n", "Classification report for turbine 4, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.010417 0.058824 0.017699 17\n", " 11 0.000000 0.000000 0.000000 144\n", " 12 0.000000 0.000000 0.000000 144\n", " 13 0.000000 0.000000 0.000000 144\n", " 14 0.000000 0.000000 0.000000 144\n", " 15 0.000000 0.000000 0.000000 144\n", " 16 0.000000 0.000000 0.000000 144\n", " 17 0.040000 0.006944 0.011834 144\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.940997 0.978358 0.959314 19268\n", " 20 0.874627 0.870082 0.872348 1347\n", "\n", "avg / total 0.886669 0.919253 0.902549 21784\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 4, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 18\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.960497 0.981139 0.970708 17496\n", " 20 0.886759 0.939090 0.912175 3694\n", "\n", "avg / total 0.921802 0.947255 0.934313 21784\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 4, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.984281 0.960971 0.972486 15117\n", " 20 0.937354 0.962802 0.949908 6667\n", "\n", "avg / total 0.969919 0.961531 0.965576 21784\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 4, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.047619 0.003876 0.007168 258\n", " 11 0.000000 0.000000 0.000000 322\n", " 12 0.000000 0.000000 0.000000 288\n", " 13 0.000000 0.000000 0.000000 280\n", " 14 0.000000 0.000000 0.000000 248\n", " 15 0.000000 0.000000 0.000000 201\n", " 16 0.000000 0.000000 0.000000 180\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.888951 0.984495 0.934287 16059\n", " 20 0.874651 0.941803 0.906986 3660\n", "\n", "avg / total 0.802845 0.884043 0.841220 21784\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 4, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.993994 0.971002 0.982363 20622\n", " 20 0.763650 0.878657 0.817127 1162\n", "\n", "avg / total 0.981707 0.966076 0.973549 21784\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 4, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.995990 0.988016 0.991987 20360\n", " 20 0.926003 0.940309 0.933101 1424\n", "\n", "avg / total 0.991415 0.984897 0.988137 21784\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 4, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.426060 0.398068 0.411588 1035\n", " 11 0.052995 0.036392 0.043152 632\n", " 12 0.021277 0.008197 0.011834 488\n", " 13 0.010840 0.008547 0.009558 468\n", " 14 0.024814 0.022472 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" 18 0.000000 0.000000 0.000000 108\n", " 19 0.953195 0.971158 0.962092 17405\n", " 20 0.789625 0.914997 0.847701 3294\n", "\n", "avg / total 0.881926 0.914341 0.896963 21784\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 4, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.846154 0.004264 0.008484 5160\n", " 11 0.000000 0.000000 0.000000 221\n", " 12 0.000000 0.000000 0.000000 190\n", " 13 0.000000 0.000000 0.000000 180\n", " 14 0.000000 0.000000 0.000000 180\n", " 15 0.000000 0.000000 0.000000 180\n", " 16 0.000000 0.000000 0.000000 180\n", " 17 0.000000 0.000000 0.000000 180\n", " 18 0.000000 0.000000 0.000000 180\n", " 19 0.887892 0.970723 0.927462 13560\n", " 20 0.205612 0.894469 0.334363 1573\n", "\n", "avg / total 0.767967 0.669849 0.603476 21784\n", "\n", "Classification report for turbine 4, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.032936 0.543307 0.062106 127\n", " 11 0.000000 0.000000 0.000000 124\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.941224 0.950155 0.945669 17073\n", " 20 0.807072 0.419006 0.551626 3704\n", "\n", "avg / total 0.875096 0.819087 0.835315 21784\n", "\n", "Classification report for turbine 4, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.178451 0.321212 0.229437 165\n", " 11 0.000000 0.000000 0.000000 179\n", " 12 0.000000 0.000000 0.000000 180\n", " 13 0.000000 0.000000 0.000000 180\n", " 14 0.000000 0.000000 0.000000 180\n", " 15 0.000000 0.000000 0.000000 180\n", " 16 0.000000 0.000000 0.000000 180\n", " 17 0.080000 0.011111 0.019512 180\n", " 18 0.000000 0.000000 0.000000 180\n", " 19 0.925517 0.977596 0.950844 19193\n", " 20 0.672762 0.708207 0.690030 987\n", "\n", "avg / total 0.847930 0.895933 0.870913 21784\n", "\n", "Classification report for turbine 4, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.484177 0.133043 0.208731 1150\n", " 11 0.000000 0.000000 0.000000 552\n", " 12 0.000000 0.000000 0.000000 540\n", " 13 0.021739 0.001880 0.003460 532\n", " 14 0.023810 0.001984 0.003663 504\n", " 15 0.120000 0.005952 0.011342 504\n", " 16 0.000000 0.000000 0.000000 476\n", " 17 0.000000 0.000000 0.000000 468\n", " 18 0.000000 0.000000 0.000000 436\n", " 19 0.804280 0.982069 0.884327 16340\n", " 20 0.188168 0.812057 0.305537 282\n", "\n", "avg / total 0.635138 0.754407 0.678733 21784\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 4, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.986179 0.983275 0.984725 17997\n", " 20 0.921615 0.934513 0.928019 3787\n", "\n", "avg / total 0.974955 0.974798 0.974867 21784\n", "\n", "Classification report for turbine 4, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.985284 0.974400 0.979812 15117\n", " 20 0.943371 0.967002 0.955040 6667\n", "\n", "avg / total 0.972457 0.972136 0.972230 21784\n", "\n", "Classification report for turbine 4, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.988815 0.988815 0.988815 17791\n", " 20 0.950163 0.950163 0.950163 3993\n", "\n", "avg / total 0.981730 0.981730 0.981730 21784\n", "\n", "Classification report for turbine 4, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.994974 0.988750 0.991852 20622\n", " 20 0.820294 0.911360 0.863433 1162\n", "\n", "avg / total 0.985656 0.984622 0.985002 21784\n", "\n", "Classification report for turbine 4, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.996804 0.995678 0.996241 20360\n", " 20 0.939185 0.954354 0.946708 1424\n", "\n", "avg / total 0.993037 0.992976 0.993003 21784\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 4, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.181818 0.070175 0.101266 57\n", " 11 0.128571 0.027778 0.045685 324\n", " 12 0.018519 0.003086 0.005291 324\n", " 13 0.000000 0.000000 0.000000 324\n", " 14 0.068182 0.009259 0.016304 324\n", " 15 0.081967 0.030864 0.044843 324\n", " 16 0.000000 0.000000 0.000000 324\n", " 17 0.000000 0.000000 0.000000 319\n", " 18 0.000000 0.000000 0.000000 288\n", " 19 0.866985 0.966479 0.914032 15781\n", " 20 0.819141 0.915169 0.864496 3395\n", "\n", "avg / total 0.760629 0.844014 0.798816 21784\n", "\n", "Classification report for turbine 4, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.055556 0.142857 0.080000 7\n", " 11 0.047297 0.194444 0.076087 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.967985 0.931034 0.949150 14906\n", " 20 0.921245 0.939997 0.930526 6583\n", "\n", "avg / total 0.940848 0.921502 0.930820 21784\n", "\n", "Classification report for turbine 4, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 12\n", " 11 0.026316 0.013889 0.018182 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.955319 0.962868 0.959079 17209\n", " 20 0.943733 0.942313 0.943022 3987\n", "\n", "avg / total 0.927499 0.933162 0.930312 21784\n", "\n", "Classification report for turbine 4, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 19\n", " 11 0.050000 0.018519 0.027027 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.955053 0.975604 0.965219 19798\n", " 20 0.770186 0.899365 0.829778 1103\n", "\n", "avg / total 0.907228 0.932290 0.919371 21784\n", "\n", "Classification report for turbine 4, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 30\n", " 11 0.000000 0.000000 0.000000 180\n", " 12 0.000000 0.000000 0.000000 180\n", " 13 0.000000 0.000000 0.000000 180\n", " 14 0.000000 0.000000 0.000000 180\n", " 15 0.058824 0.005556 0.010152 180\n", " 16 0.000000 0.000000 0.000000 180\n", " 17 0.000000 0.000000 0.000000 180\n", " 18 0.000000 0.000000 0.000000 176\n", " 19 0.939957 0.982807 0.960905 19194\n", " 20 0.730825 0.898577 0.806065 1124\n", "\n", "avg / total 0.866396 0.912367 0.888333 21784\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 4, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.986215 0.981886 0.984046 17997\n", " 20 0.915675 0.934777 0.925127 3787\n", "\n", "avg / total 0.973952 0.973696 0.973803 21784\n", "\n", "Classification report for turbine 4, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.984378 0.975392 0.979864 15117\n", " 20 0.945334 0.964902 0.955018 6667\n", "\n", "avg / total 0.972429 0.972181 0.972260 21784\n", "\n", "Classification report for turbine 4, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.990868 0.987971 0.989417 17791\n", " 20 0.947095 0.959429 0.953222 3993\n", "\n", "avg / total 0.982844 0.982740 0.982783 21784\n", "\n", "Classification report for turbine 4, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.995476 0.992387 0.993929 20622\n", " 20 0.871941 0.919966 0.895310 1162\n", "\n", "avg / total 0.988887 0.988524 0.988669 21784\n", "\n", "Classification report for turbine 4, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.997096 0.995039 0.996067 20360\n", " 20 0.931105 0.958567 0.944637 1424\n", "\n", "avg / total 0.992782 0.992655 0.992705 21784\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 4, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.985336 0.981941 0.983636 17997\n", " 20 0.915562 0.930552 0.922996 3787\n", "\n", "avg / total 0.973206 0.973008 0.973094 21784\n", "\n", "Classification report for turbine 4, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.983468 0.975921 0.979680 15117\n", " 20 0.946336 0.962802 0.954498 6667\n", "\n", "avg / total 0.972104 0.971906 0.971973 21784\n", "\n", "Classification report for turbine 4, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.989411 0.987353 0.988381 17791\n", " 20 0.944169 0.952918 0.948523 3993\n", "\n", "avg / total 0.981118 0.981041 0.981075 21784\n", "\n", "Classification report for turbine 4, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 50\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 77\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.964129 0.990586 0.977178 19970\n", " 20 0.781201 0.920000 0.844938 1075\n", "\n", "avg / total 0.922395 0.953498 0.937503 21784\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 4, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.995786 0.986444 0.991093 20360\n", " 20 0.921488 0.939607 0.930459 1424\n", "\n", "avg / total 0.990929 0.983382 0.987129 21784\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 5, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 28\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 8\n", " 19 0.955136 0.993537 0.973958 18878\n", " 20 0.931129 0.625926 0.748616 1620\n", "\n", "avg / total 0.940031 0.951121 0.942901 20786\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 5, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 18\n", " 11 0.000000 0.000000 0.000000 40\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 56\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.966401 0.984198 0.975218 17593\n", " 20 0.901748 0.961237 0.930543 2683\n", "\n", "avg / total 0.934344 0.957087 0.945524 20786\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 5, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 107\n", " 11 0.000000 0.000000 0.000000 144\n", " 12 0.000000 0.000000 0.000000 144\n", " 13 0.111111 0.016129 0.028169 124\n", " 14 0.000000 0.000000 0.000000 91\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.953066 0.989493 0.970938 17608\n", " 20 0.912786 0.889439 0.900961 2424\n", "\n", "avg / total 0.914460 0.942028 0.927725 20786\n", "\n", "Classification report for turbine 5, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.989154 0.992020 0.990584 19673\n", " 20 0.942736 0.798742 0.864786 1113\n", "\n", "avg / total 0.986668 0.981670 0.983849 20786\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 5, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.500000 0.009709 0.019048 103\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.974341 0.996438 0.985266 19931\n", " 20 0.872000 0.704741 0.779499 464\n", "\n", "avg / total 0.956206 0.971231 0.962233 20786\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 5, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.008929 0.016949 0.011696 59\n", " 11 0.005405 0.005556 0.005479 180\n", " 12 0.008197 0.011111 0.009434 180\n", " 13 0.000000 0.000000 0.000000 180\n", " 14 0.000000 0.000000 0.000000 180\n", " 15 0.010909 0.016667 0.013187 180\n", " 16 0.014574 0.072222 0.024254 180\n", " 17 0.038462 0.005556 0.009709 180\n", " 18 0.000000 0.000000 0.000000 180\n", " 19 0.895637 0.907059 0.901312 17721\n", " 20 0.894581 0.579821 0.703603 1566\n", "\n", "avg / total 0.831665 0.818003 0.821989 20786\n", "\n", "Classification report for turbine 5, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.005051 0.008475 0.006329 118\n", " 11 0.000000 0.000000 0.000000 144\n", " 12 0.035088 0.013889 0.019900 144\n", " 13 0.000000 0.000000 0.000000 144\n", " 14 0.000000 0.000000 0.000000 144\n", " 15 0.017241 0.006944 0.009901 144\n", " 16 0.006250 0.006944 0.006579 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.924013 0.955773 0.939625 16845\n", " 20 0.893698 0.881318 0.887465 2671\n", "\n", "avg / total 0.864096 0.888050 0.875800 20786\n", "\n", "Classification report for turbine 5, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 12\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.023810 0.027778 0.025641 36\n", " 14 0.350000 0.583333 0.437500 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.974051 0.974974 0.974512 17941\n", " 20 0.954715 0.902947 0.928110 2545\n", "\n", "avg / total 0.958272 0.953142 0.955568 20786\n", "\n", "Classification report for turbine 5, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 25\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.973773 0.981009 0.977378 19378\n", " 20 0.915523 0.791781 0.849167 1095\n", "\n", "avg / total 0.956041 0.956269 0.955906 20786\n", "\n", "Classification report for turbine 5, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.993878 0.990845 0.992359 20317\n", " 20 0.877551 0.733475 0.799071 469\n", "\n", "avg / total 0.991253 0.985038 0.987998 20786\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 5, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.990746 0.995248 0.992992 19148\n", " 20 0.941328 0.891331 0.915648 1638\n", "\n", "avg / total 0.986852 0.987059 0.986897 20786\n", "\n", "Classification report for turbine 5, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.993979 0.985789 0.989867 18085\n", " 20 0.909825 0.960015 0.934246 2701\n", "\n", "avg / total 0.983043 0.982440 0.982639 20786\n", "\n", "Classification report for turbine 5, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.989618 0.994181 0.991894 18217\n", " 20 0.957344 0.926041 0.941433 2569\n", "\n", "avg / total 0.985629 0.985760 0.985658 20786\n", "\n", "Classification report for turbine 5, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.990403 0.996696 0.993540 19673\n", " 20 0.934211 0.829290 0.878629 1113\n", "\n", "avg / total 0.987394 0.987732 0.987387 20786\n", "\n", "Classification report for turbine 5, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.994260 0.997441 0.995848 20317\n", " 20 0.871287 0.750533 0.806415 469\n", "\n", "avg / total 0.991485 0.991870 0.991573 20786\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 5, turbine category 5.0\n", 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precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 697\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.977342 0.984208 0.980763 17794\n", " 20 0.690710 0.944694 0.797980 2007\n", "\n", "avg / total 0.903353 0.933753 0.916638 20786\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 5, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 6\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.971976 0.992359 0.982062 17930\n", " 20 0.975386 0.912568 0.942932 2562\n", "\n", "avg / total 0.958649 0.968488 0.963349 20786\n", "\n", "Classification report for turbine 5, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 7\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.976921 0.992170 0.984486 19412\n", " 20 0.909958 0.796108 0.849234 1079\n", "\n", "avg / total 0.959580 0.967911 0.963493 20786\n", "\n", "Classification report for turbine 5, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.991945 0.994094 0.993018 20317\n", " 20 0.856287 0.609808 0.712329 469\n", "\n", "avg / total 0.988884 0.985423 0.986685 20786\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being 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0\n", " 19 0.989149 0.995773 0.992450 18217\n", " 20 0.968929 0.922538 0.945165 2569\n", "\n", "avg / total 0.986650 0.986722 0.986606 20786\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 5, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 19 0.990405 0.996848 0.993616 19673\n", " 20 0.939796 0.827493 0.880076 1113\n", "\n", "avg / total 0.987695 0.987780 0.987536 20786\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program 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average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 5, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 19 0.992081 0.994464 0.993271 19148\n", " 20 0.933417 0.907204 0.920124 1638\n", "\n", "avg / total 0.987458 0.987588 0.987507 20786\n", "\n", "Classification report for turbine 5, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 19 0.993364 0.985015 0.989172 18085\n", " 20 0.905012 0.955942 0.929780 2701\n", "\n", "avg / total 0.981883 0.981237 0.981455 20786\n", "\n", "Classification report for turbine 5, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 19 0.988224 0.995005 0.991603 18217\n", " 20 0.962766 0.915921 0.938759 2569\n", "\n", "avg / total 0.985077 0.985230 0.985072 20786\n", "\n", "Classification report for turbine 5, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 19 0.990605 0.996899 0.993742 19673\n", " 20 0.938259 0.832884 0.882437 1113\n", "\n", "avg / total 0.987802 0.988117 0.987782 20786\n", "\n", "Classification report for turbine 5, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 19 0.994407 0.997539 0.995970 20317\n", " 20 0.876543 0.756930 0.812357 469\n", "\n", "avg / total 0.991747 0.992110 0.991827 20786\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 5, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 1941\n", " 11 0.000000 0.000000 0.000000 252\n", " 12 0.000000 0.000000 0.000000 265\n", " 13 0.013514 0.003663 0.005764 273\n", " 14 0.010309 0.004630 0.006390 216\n", " 15 0.012987 0.004630 0.006826 216\n", " 16 0.000000 0.000000 0.000000 185\n", " 17 0.000000 0.000000 0.000000 163\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.810011 0.964775 0.880645 16068\n", " 20 0.823583 0.847601 0.835420 1063\n", "\n", "avg / total 0.668693 0.789281 0.723693 20786\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 5, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.007519 0.012658 0.009434 79\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.008772 0.013889 0.010753 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.968532 0.961122 0.964813 17645\n", " 20 0.824757 0.921963 0.870655 2486\n", "\n", "avg / total 0.920876 0.926248 0.923222 20786\n", "\n", "Classification report for turbine 5, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.107527 0.243902 0.149254 41\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.028571 0.009259 0.013986 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 78\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.944126 0.978618 0.961062 17491\n", " 20 0.963093 0.867089 0.912573 2528\n", "\n", "avg / total 0.911955 0.929472 0.920069 20786\n", "\n", "Classification report for turbine 5, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.066265 0.063953 0.065089 172\n", " 11 0.000000 0.000000 0.000000 311\n", " 12 0.000000 0.000000 0.000000 187\n", " 13 0.000000 0.000000 0.000000 167\n", " 14 0.000000 0.000000 0.000000 144\n", " 15 0.000000 0.000000 0.000000 144\n", " 16 0.000000 0.000000 0.000000 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.000000 0.000000 0.000000 112\n", " 19 0.921422 0.981503 0.950514 18327\n", " 20 0.742664 0.704497 0.723077 934\n", "\n", "avg / total 0.846336 0.897575 0.871097 20786\n", "\n", "Classification report for turbine 5, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.047619 0.043478 0.045455 23\n", " 11 0.052632 0.013889 0.021978 144\n", " 12 0.000000 0.000000 0.000000 144\n", " 13 0.000000 0.000000 0.000000 144\n", " 14 0.050000 0.006944 0.012195 144\n", " 15 0.000000 0.000000 0.000000 144\n", " 16 0.000000 0.000000 0.000000 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.938019 0.989528 0.963085 19194\n", " 20 0.805310 0.654676 0.722222 417\n", "\n", "avg / total 0.883095 0.927066 0.904098 20786\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 5, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.055556 0.023810 0.033333 84\n", " 11 0.000000 0.000000 0.000000 103\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 61\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.967084 0.957065 0.962048 18726\n", " 20 0.866445 0.855643 0.861010 1524\n", "\n", "avg / total 0.934992 0.925046 0.929967 20786\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 5, turbine category 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0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.989452 0.996543 0.992985 19673\n", " 20 0.942649 0.812219 0.872587 1113\n", "\n", "avg / total 0.986946 0.986674 0.986538 20786\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 5, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.993966 0.997342 0.995651 20317\n", " 20 0.890909 0.731343 0.803279 469\n", "\n", "avg / total 0.991641 0.991340 0.991311 20786\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 5, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.234133 0.264753 0.248503 627\n", " 11 0.000000 0.000000 0.000000 724\n", " 12 0.061538 0.007030 0.012618 569\n", " 13 0.043011 0.015209 0.022472 526\n", " 14 0.018868 0.002008 0.003630 498\n", " 15 0.000000 0.000000 0.000000 468\n", " 16 0.032258 0.002212 0.004141 452\n", " 17 0.000000 0.000000 0.000000 432\n", " 18 0.000000 0.000000 0.000000 397\n", " 19 0.771504 0.960721 0.855778 14919\n", " 20 0.724572 0.685690 0.704595 1174\n", "\n", "avg / total 0.605654 0.736938 0.662611 20786\n", "\n", "Classification report for turbine 5, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.339227 0.528399 0.413190 581\n", " 11 0.032895 0.034364 0.033613 291\n", " 12 0.000000 0.000000 0.000000 288\n", " 13 0.025862 0.010417 0.014851 288\n", " 14 0.000000 0.000000 0.000000 288\n", " 15 0.042553 0.020833 0.027972 288\n", " 16 0.006250 0.003472 0.004464 288\n", " 17 0.015660 0.024306 0.019048 288\n", " 18 0.000000 0.000000 0.000000 245\n", " 19 0.868421 0.880056 0.874200 15824\n", " 20 0.796626 0.803023 0.799812 2117\n", "\n", "avg / total 0.753441 0.767824 0.759910 20786\n", "\n", "Classification report for turbine 5, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.074766 0.505747 0.130274 174\n", " 11 0.000000 0.000000 0.000000 144\n", " 12 0.012766 0.020833 0.015831 144\n", " 13 0.025316 0.013889 0.017937 144\n", " 14 0.014085 0.020833 0.016807 144\n", " 15 0.008065 0.006944 0.007463 144\n", " 16 0.009901 0.006944 0.008163 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.036364 0.013889 0.020101 144\n", " 19 0.921199 0.924060 0.922627 17066\n", " 20 0.935185 0.548454 0.691417 2394\n", "\n", "avg / total 0.865407 0.826662 0.838829 20786\n", "\n", "Classification report for turbine 5, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.255507 0.256071 0.255788 453\n", " 11 0.027027 0.006135 0.010000 652\n", " 12 0.034483 0.005780 0.009901 519\n", " 13 0.050000 0.008547 0.014599 468\n", " 14 0.039370 0.011574 0.017889 432\n", " 15 0.013514 0.002457 0.004158 407\n", " 16 0.017857 0.002525 0.004425 396\n", " 17 0.000000 0.000000 0.000000 364\n", " 18 0.000000 0.000000 0.000000 332\n", " 19 0.803312 0.957391 0.873609 15912\n", " 20 0.719219 0.562867 0.631510 851\n", "\n", "avg / total 0.654219 0.762388 0.701618 20786\n", "\n", "Classification report for turbine 5, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.755906 0.379447 0.505263 253\n", " 11 0.048000 0.033333 0.039344 180\n", " 12 0.019608 0.011173 0.014235 179\n", " 13 0.008547 0.006944 0.007663 144\n", " 14 0.017094 0.013889 0.015326 144\n", " 15 0.020202 0.013889 0.016461 144\n", " 16 0.013889 0.013889 0.013889 144\n", " 17 0.029851 0.013889 0.018957 144\n", " 18 0.013514 0.006944 0.009174 144\n", " 19 0.931860 0.956932 0.944229 18993\n", " 20 0.593548 0.580442 0.586922 317\n", "\n", "avg / total 0.871029 0.888723 0.878909 20786\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 5, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.325416 0.467577 0.383754 879\n", " 11 0.002088 0.001815 0.001942 551\n", " 12 0.138462 0.018480 0.032609 487\n", " 13 0.007752 0.002137 0.003350 468\n", " 14 0.024048 0.025641 0.024819 468\n", " 15 0.021505 0.004577 0.007547 437\n", " 16 0.010753 0.005556 0.007326 360\n", " 17 0.000000 0.000000 0.000000 344\n", " 18 0.000000 0.000000 0.000000 288\n", " 19 0.807124 0.898957 0.850569 15627\n", " 20 0.365297 0.182440 0.243346 877\n", "\n", "avg / total 0.640627 0.704609 0.667692 20786\n", "\n", "Classification report for turbine 5, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.206180 0.382789 0.268006 1011\n", " 11 0.015873 0.004777 0.007344 628\n", " 12 0.068627 0.028283 0.040057 495\n", " 13 0.039130 0.022556 0.028617 399\n", " 14 0.021212 0.019718 0.020438 355\n", " 15 0.004132 0.003086 0.003534 324\n", " 16 0.000000 0.000000 0.000000 324\n", " 17 0.000000 0.000000 0.000000 324\n", " 18 0.000000 0.000000 0.000000 324\n", " 19 0.844136 0.918142 0.879585 14965\n", " 20 0.656863 0.450214 0.534252 1637\n", "\n", "avg / total 0.672792 0.716732 0.690502 20786\n", "\n", "Classification report for turbine 5, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.171841 0.652055 0.272000 365\n", " 11 0.011321 0.013889 0.012474 216\n", " 12 0.000000 0.000000 0.000000 216\n", " 13 0.000000 0.000000 0.000000 210\n", " 14 0.000000 0.000000 0.000000 180\n", " 15 0.000000 0.000000 0.000000 180\n", " 16 0.000000 0.000000 0.000000 180\n", " 17 0.000000 0.000000 0.000000 180\n", " 18 0.000000 0.000000 0.000000 149\n", " 19 0.904097 0.922893 0.913398 16691\n", " 20 0.896373 0.545741 0.678431 2219\n", "\n", "avg / total 0.824810 0.810930 0.810783 20786\n", "\n", "Classification report for turbine 5, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.199324 0.374603 0.260198 315\n", " 11 0.013100 0.009375 0.010929 320\n", " 12 0.009259 0.004274 0.005848 234\n", " 13 0.000000 0.000000 0.000000 216\n", " 14 0.011905 0.005495 0.007519 182\n", " 15 0.000000 0.000000 0.000000 180\n", " 16 0.013699 0.005556 0.007905 180\n", " 17 0.000000 0.000000 0.000000 180\n", " 18 0.012195 0.005556 0.007634 180\n", " 19 0.899904 0.944395 0.921613 17840\n", " 20 0.854890 0.565172 0.680477 959\n", "\n", "avg / total 0.815457 0.842634 0.826765 20786\n", "\n", "Classification report for turbine 5, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 4\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.979600 0.961310 0.970369 20031\n", " 20 0.878338 0.639309 0.740000 463\n", "\n", "avg / total 0.963583 0.940633 0.951606 20786\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 5, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.970692 0.994569 0.982485 19148\n", " 20 0.910883 0.648962 0.757932 1638\n", "\n", "avg / total 0.965979 0.967334 0.964790 20786\n", "\n", "Classification report for turbine 5, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.994749 0.984683 0.989691 18085\n", " 20 0.903953 0.965198 0.933572 2701\n", "\n", "avg / total 0.982951 0.982151 0.982398 20786\n", "\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 5, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.989683 0.995279 0.992473 18217\n", " 20 0.965126 0.926431 0.945382 2569\n", "\n", "avg / total 0.986648 0.986770 0.986653 20786\n", "\n", "Classification report for turbine 5, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.990752 0.996594 0.993665 19673\n", " 20 0.932798 0.835580 0.881517 1113\n", "\n", "avg / total 0.987649 0.987973 0.987660 20786\n", "\n", "Classification report for turbine 5, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.994016 0.997539 0.995775 20317\n", " 20 0.874055 0.739872 0.801386 469\n", "\n", "avg / total 0.991310 0.991725 0.991389 20786\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 5, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 34\n", " 11 0.000000 0.000000 0.000000 180\n", " 12 0.000000 0.000000 0.000000 180\n", " 13 0.000000 0.000000 0.000000 180\n", " 14 0.000000 0.000000 0.000000 180\n", " 15 0.000000 0.000000 0.000000 180\n", " 16 0.000000 0.000000 0.000000 174\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.922932 0.992927 0.956651 17814\n", " 20 0.919005 0.914340 0.916667 1576\n", "\n", "avg / total 0.860650 0.920283 0.889370 20786\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 5, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.333333 0.076923 0.125000 13\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.280000 0.097222 0.144330 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.959644 0.979546 0.969493 17503\n", " 20 0.947349 0.941722 0.944527 2694\n", "\n", "avg / total 0.932036 0.947272 0.939364 20786\n", "\n", "Classification report for turbine 5, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 12\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.949212 0.986954 0.967715 17630\n", " 20 0.980287 0.852025 0.911667 2568\n", "\n", "avg / total 0.926199 0.942365 0.933416 20786\n", "\n", "Classification report for turbine 5, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 22\n", " 11 0.043478 0.006944 0.011976 144\n", " 12 0.000000 0.000000 0.000000 144\n", " 13 0.000000 0.000000 0.000000 144\n", " 14 0.000000 0.000000 0.000000 144\n", " 15 0.000000 0.000000 0.000000 144\n", " 16 0.019048 0.013889 0.016064 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.933060 0.983653 0.957689 18535\n", " 20 0.916838 0.829155 0.870795 1077\n", "\n", "avg / total 0.879953 0.920235 0.899290 20786\n", "\n", "Classification report for turbine 5, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.993276 0.988778 0.991022 20317\n", " 20 0.895604 0.695096 0.782713 469\n", "\n", "avg / total 0.991072 0.982151 0.986322 20786\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 5, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.969658 0.996396 0.982846 19148\n", " 20 0.937838 0.635531 0.757642 1638\n", "\n", "avg / total 0.967151 0.967959 0.965099 20786\n", "\n", "Classification report for turbine 5, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.992979 0.985292 0.989120 18085\n", " 20 0.906371 0.953351 0.929267 2701\n", "\n", "avg / total 0.981724 0.981141 0.981343 20786\n", "\n", "Classification report for turbine 5, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.988497 0.995334 0.991904 18217\n", " 20 0.965207 0.917867 0.940942 2569\n", "\n", "avg / total 0.985618 0.985760 0.985605 20786\n", "\n", "Classification report for turbine 5, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.990956 0.997001 0.993969 19673\n", " 20 0.940584 0.839173 0.886990 1113\n", "\n", "avg / total 0.988259 0.988550 0.988241 20786\n", "\n", "Classification report for turbine 5, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.993819 0.997194 0.995504 20317\n", " 20 0.857500 0.731343 0.789413 469\n", "\n", "avg / total 0.990743 0.991196 0.990854 20786\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 5, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.992304 0.996553 0.994424 19148\n", " 20 0.957584 0.909646 0.932999 1638\n", "\n", "avg / total 0.989568 0.989705 0.989583 20786\n", "\n", "Classification report for turbine 5, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.995137 0.984518 0.989799 18085\n", " 20 0.903248 0.967790 0.934406 2701\n", "\n", "avg / total 0.983197 0.982344 0.982601 20786\n", "\n", "Classification report for turbine 5, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.989802 0.996322 0.993051 18217\n", " 20 0.972642 0.927209 0.949382 2569\n", "\n", "avg / total 0.987681 0.987780 0.987654 20786\n", "\n", "Classification report for turbine 5, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 12\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.976064 0.997214 0.986526 19383\n", " 20 0.932859 0.831369 0.879195 1103\n", "\n", "avg / total 0.959684 0.974021 0.966592 20786\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 5, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.993865 0.996751 0.995306 20317\n", " 20 0.898172 0.733475 0.807512 469\n", "\n", "avg / total 0.991706 0.990811 0.991069 20786\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 6, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 19 0.939413 0.985621 0.961963 19334\n", " 20 0.817824 0.503835 0.623532 2477\n", "\n", "avg / total 0.925605 0.930906 0.923528 21811\n", "\n", "Classification report for turbine 6, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 19 0.994217 0.987522 0.990858 20195\n", " 20 0.856164 0.928218 0.890736 1616\n", "\n", "avg / total 0.983989 0.983128 0.983440 21811\n", "\n", "Classification report for turbine 6, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 19 0.918162 0.969057 0.942923 14252\n", " 20 0.934850 0.837148 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"------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 6, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 119\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.932255 0.986464 0.958594 18986\n", " 20 0.801278 0.570306 0.666345 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"avg / total 0.982973 0.977809 0.980249 21811\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 6, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 54\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 101\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.889204 0.965881 0.925958 13951\n", " 20 0.889393 0.824520 0.855729 7129\n", "\n", "avg / total 0.859464 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0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.200000 0.013889 0.025974 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.956708 0.989844 0.972994 19200\n", " 20 0.812269 0.847682 0.829598 1812\n", "\n", "avg / total 0.910321 0.941818 0.925523 21811\n", "\n", "Classification report for turbine 6, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 26\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.980613 0.991187 0.985871 20310\n", " 20 0.889655 0.869419 0.879421 1187\n", "\n", "avg / total 0.961545 0.970290 0.965885 21811\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 6, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 19 0.939431 0.985932 0.962120 19334\n", " 20 0.821053 0.503835 0.624468 2477\n", "\n", "avg / total 0.925987 0.931182 0.923774 21811\n", "\n", "Classification report for turbine 6, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 19 0.994019 0.987472 0.990735 20195\n", " 20 0.855346 0.925743 0.889153 1616\n", "\n", "avg / total 0.983744 0.982899 0.983208 21811\n", "\n", "Classification report for turbine 6, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 19 0.920675 0.968285 0.943880 14252\n", " 20 0.933744 0.842704 0.885891 7559\n", "\n", "avg / total 0.925204 0.924763 0.923783 21811\n", "\n", "Classification report for turbine 6, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 102\n", " 11 0.000000 0.000000 0.000000 158\n", " 12 0.000000 0.000000 0.000000 92\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 46\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.963656 0.992431 0.977832 19290\n", " 20 0.881748 0.899318 0.890447 1907\n", "\n", "avg / total 0.929367 0.956352 0.942665 21811\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 6, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 13\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.983059 0.992773 0.987892 20341\n", " 20 0.891286 0.918734 0.904802 1169\n", "\n", "avg / total 0.964574 0.975104 0.969806 21811\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 6, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 128\n", " 11 0.000000 0.000000 0.000000 159\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.911231 0.986485 0.947366 18720\n", " 20 0.581230 0.438477 0.499861 2048\n", "\n", "avg / total 0.836669 0.887855 0.860043 21811\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 6, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.228916 0.033159 0.057927 573\n", " 11 0.000000 0.000000 0.000000 250\n", " 12 0.076923 0.004630 0.008734 216\n", " 13 0.000000 0.000000 0.000000 195\n", " 14 0.000000 0.000000 0.000000 180\n", " 15 0.125000 0.011111 0.020408 180\n", " 16 0.000000 0.000000 0.000000 180\n", " 17 0.000000 0.000000 0.000000 180\n", " 18 0.000000 0.000000 0.000000 169\n", " 19 0.917092 0.974776 0.945054 18633\n", " 20 0.541741 0.867299 0.666910 1055\n", "\n", "avg / total 0.817477 0.875705 0.841389 21811\n", "\n", "Classification report for turbine 6, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.129381 0.304982 0.181687 823\n", " 11 0.000000 0.000000 0.000000 144\n", " 12 0.035714 0.006944 0.011628 144\n", " 13 0.000000 0.000000 0.000000 117\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.008000 0.009259 0.008584 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 91\n", " 19 0.920188 0.949695 0.934709 13597\n", " 20 0.799088 0.677549 0.733317 6463\n", "\n", "avg / total 0.815588 0.804411 0.806968 21811\n", "\n", "Classification report for turbine 6, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 11\n", " 11 0.000000 0.000000 0.000000 64\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.973780 0.977855 0.975813 19598\n", " 20 0.875177 0.654295 0.748786 1886\n", "\n", "avg / total 0.950655 0.935216 0.941553 21811\n", "\n", "Classification report for turbine 6, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.298077 0.218310 0.252033 142\n", " 11 0.009804 0.003968 0.005650 252\n", " 12 0.000000 0.000000 0.000000 252\n", " 13 0.033898 0.007937 0.012862 252\n", " 14 0.000000 0.000000 0.000000 252\n", " 15 0.000000 0.000000 0.000000 252\n", " 16 0.000000 0.000000 0.000000 252\n", " 17 0.000000 0.000000 0.000000 252\n", " 18 0.000000 0.000000 0.000000 252\n", " 19 0.896795 0.980273 0.936678 18553\n", " 20 0.848548 0.743636 0.792636 1100\n", "\n", "avg / total 0.808077 0.872908 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0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.912560 0.969350 0.940098 13964\n", " 20 0.897965 0.863323 0.880303 7258\n", "\n", "avg / total 0.883060 0.907891 0.894813 21811\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 6, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 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0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.911895 0.939728 0.925602 14252\n", " 20 0.941061 0.699167 0.802277 7559\n", "\n", "avg / total 0.922003 0.856357 0.882862 21811\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 6, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.986039 0.984744 0.985391 19795\n", " 20 0.918379 0.775794 0.841086 2016\n", "\n", "avg / total 0.979785 0.965430 0.972053 21811\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 6, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.009434 0.080000 0.016878 25\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.052632 0.009259 0.015748 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.961973 0.989194 0.975393 19896\n", " 20 0.763602 0.793372 0.778203 1026\n", "\n", "avg / total 0.913703 0.939801 0.926458 21811\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 6, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.765273 0.415116 0.538259 1720\n", " 11 0.006421 0.012422 0.008466 322\n", " 12 0.000000 0.000000 0.000000 221\n", " 13 0.023529 0.018519 0.020725 216\n", " 14 0.000000 0.000000 0.000000 201\n", " 15 0.000000 0.000000 0.000000 180\n", " 16 0.032787 0.011111 0.016598 180\n", " 17 0.066667 0.016667 0.026667 180\n", " 18 0.008772 0.005556 0.006803 180\n", " 19 0.860866 0.897002 0.878563 17748\n", " 20 0.600267 0.677225 0.636428 663\n", "\n", "avg / total 0.780319 0.783871 0.777438 21811\n", "\n", "Classification report for turbine 6, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.003770 1.000000 0.007512 4\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.992711 0.952622 0.972253 20157\n", " 20 0.801233 0.381791 0.517156 1362\n", "\n", "avg / total 0.967464 0.904406 0.930819 21811\n", "\n", "Classification report for turbine 6, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.098982 0.269231 0.144748 650\n", " 11 0.000000 0.000000 0.000000 73\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 101\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 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0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.083333 0.009259 0.016667 108\n", " 19 0.954852 0.988480 0.971375 19791\n", " 20 0.529924 0.716176 0.609131 680\n", "\n", "avg / total 0.896520 0.925038 0.908467 21811\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 6, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 4\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.926037 0.984990 0.954604 19054\n", " 20 0.806995 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recall f1-score support\n", "\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 19 0.988335 0.992978 0.990651 19795\n", " 20 0.929651 0.884921 0.906734 2016\n", "\n", "avg / total 0.982911 0.982990 0.982894 21811\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 6, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 12 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 19 0.995342 0.996164 0.995753 20594\n", " 20 0.935726 0.921118 0.928364 1217\n", "\n", "avg / total 0.992016 0.991977 0.991993 21811\n", "\n", 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"\n", "avg / total 0.905535 0.897896 0.901489 21811\n", "\n", "Classification report for turbine 6, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.064516 0.058824 0.061538 34\n", " 11 0.086957 0.018519 0.030534 216\n", " 12 0.033333 0.004630 0.008130 216\n", " 13 0.038462 0.004630 0.008264 216\n", " 14 0.011696 0.018519 0.014337 216\n", " 15 0.000000 0.000000 0.000000 216\n", " 16 0.012048 0.004630 0.006689 216\n", " 17 0.000000 0.000000 0.000000 216\n", " 18 0.000000 0.000000 0.000000 216\n", " 19 0.821695 0.923789 0.869756 12636\n", " 20 0.920180 0.853770 0.885732 7413\n", "\n", "avg / total 0.790695 0.825959 0.805692 21811\n", "\n", "Classification report for turbine 6, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.038462 0.041667 0.040000 24\n", " 11 0.073684 0.048611 0.058577 144\n", " 12 0.000000 0.000000 0.000000 144\n", " 13 0.000000 0.000000 0.000000 144\n", " 14 0.000000 0.000000 0.000000 144\n", " 15 0.000000 0.000000 0.000000 144\n", " 16 0.000000 0.000000 0.000000 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.932319 0.966988 0.949337 18690\n", " 20 0.885653 0.844216 0.864438 1945\n", "\n", "avg / total 0.878418 0.904268 0.891011 21811\n", "\n", "Classification report for turbine 6, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 12\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.068966 0.027778 0.039604 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.966285 0.977284 0.971753 20030\n", " 20 0.901639 0.829841 0.864251 1193\n", "\n", "avg / total 0.936927 0.942965 0.939807 21811\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 6, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.944832 0.987690 0.965786 19334\n", " 20 0.851250 0.549859 0.668138 2477\n", "\n", "avg / total 0.934204 0.937967 0.931983 21811\n", "\n", "Classification report for turbine 6, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.994861 0.987324 0.991078 20195\n", " 20 0.855285 0.936262 0.893944 1616\n", "\n", "avg / total 0.984520 0.983540 0.983881 21811\n", "\n", "Classification report for turbine 6, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.934933 0.967864 0.951114 14252\n", " 20 0.935100 0.872999 0.902983 7559\n", "\n", "avg / total 0.934991 0.934987 0.934433 21811\n", "\n", "Classification report for turbine 6, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.988688 0.993433 0.991055 19795\n", " 20 0.932327 0.888393 0.909830 2016\n", "\n", "avg / total 0.983478 0.983724 0.983547 21811\n", "\n", "Classification report for turbine 6, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.995484 0.995484 0.995484 20594\n", " 20 0.923583 0.923583 0.923583 1217\n", "\n", "avg / total 0.991472 0.991472 0.991472 21811\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 6, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.940936 0.986294 0.963081 19334\n", " 20 0.828479 0.516754 0.636499 2477\n", "\n", "avg / total 0.928164 0.932970 0.925992 21811\n", "\n", "Classification report for turbine 6, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.994561 0.986878 0.990704 20195\n", " 20 0.850451 0.932550 0.889610 1616\n", "\n", "avg / total 0.983883 0.982853 0.983214 21811\n", "\n", "Classification report for turbine 6, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.957728 0.966531 0.962109 14252\n", " 20 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"\n", "avg / total 0.982456 0.858959 0.915769 20923\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 7, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 19 0.872393 0.925463 0.898145 8318\n", " 20 0.948756 0.910670 0.929323 12605\n", "\n", "avg / total 0.918398 0.916551 0.916928 20923\n", "\n", "Classification report for turbine 7, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 19 0.975583 0.766146 0.858272 16010\n", " 20 0.551617 0.937513 0.694564 4913\n", "\n", "avg / total 0.876030 0.806385 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0.000000 2058\n", " 11 0.000000 0.000000 0.000000 378\n", " 12 0.000000 0.000000 0.000000 161\n", " 13 0.000000 0.000000 0.000000 138\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.665190 0.907731 0.767761 6286\n", " 20 0.868449 0.943584 0.904459 11362\n", "\n", "avg / total 0.671448 0.785117 0.721818 20923\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 7, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.002597 0.461538 0.005166 13\n", " 11 0.021331 0.231481 0.039062 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.938131 0.706424 0.805955 15519\n", " 20 0.439464 0.506737 0.470709 4527\n", "\n", "avg / total 0.791026 0.635091 0.699842 20923\n", "\n", "Classification report for turbine 7, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.038043 0.064815 0.047945 108\n", " 11 0.045455 0.003185 0.005952 314\n", " 12 0.000000 0.000000 0.000000 252\n", " 13 0.000000 0.000000 0.000000 252\n", " 14 0.000000 0.000000 0.000000 189\n", " 15 0.025641 0.005556 0.009132 180\n", " 16 0.000000 0.000000 0.000000 180\n", " 17 0.000000 0.000000 0.000000 180\n", " 18 0.000000 0.000000 0.000000 180\n", " 19 0.882121 0.948920 0.914302 15094\n", " 20 0.904947 0.874812 0.889624 3994\n", "\n", "avg / total 0.810213 0.851981 0.829820 20923\n", "\n", "Classification report for turbine 7, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.984298 0.925597 0.954046 19166\n", " 20 0.868750 0.791121 0.828120 1757\n", "\n", "avg / total 0.974595 0.914305 0.943471 20923\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 7, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 36\n", " 11 0.000000 0.000000 0.000000 145\n", " 12 0.000000 0.000000 0.000000 144\n", " 13 0.000000 0.000000 0.000000 144\n", " 14 0.027027 0.006944 0.011050 144\n", " 15 0.000000 0.000000 0.000000 144\n", " 16 0.000000 0.000000 0.000000 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.934762 0.982625 0.958096 18417\n", " 20 0.834981 0.833713 0.834347 1317\n", "\n", "avg / total 0.875548 0.917459 0.895937 20923\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 7, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 19 0.886957 0.931955 0.908899 8318\n", " 20 0.953542 0.921618 0.937308 12605\n", "\n", "avg / total 0.927071 0.925728 0.926014 20923\n", "\n", "Classification report for turbine 7, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 19 0.980345 0.766396 0.860268 16010\n", " 20 0.555133 0.949929 0.700751 4913\n", "\n", "avg / total 0.880500 0.809492 0.822811 20923\n", "\n", "Classification report for turbine 7, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 19 0.978139 0.984926 0.981521 16718\n", " 20 0.938371 0.912485 0.925247 4205\n", "\n", "avg / total 0.970147 0.970368 0.970212 20923\n", "\n", "Classification report for turbine 7, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 19 0.990238 0.989669 0.989953 19166\n", " 20 0.888009 0.893569 0.890780 1757\n", "\n", "avg / total 0.981653 0.981599 0.981625 20923\n", "\n", "Classification report for turbine 7, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 19 0.993234 0.993132 0.993183 19512\n", " 20 0.905166 0.906449 0.905807 1411\n", "\n", "avg / total 0.987295 0.987287 0.987291 20923\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 7, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 927\n", " 11 0.000000 0.000000 0.000000 324\n", " 12 0.000000 0.000000 0.000000 302\n", " 13 0.000000 0.000000 0.000000 257\n", " 14 0.000000 0.000000 0.000000 241\n", " 15 0.000000 0.000000 0.000000 216\n", " 16 0.000000 0.000000 0.000000 216\n", " 17 0.000000 0.000000 0.000000 216\n", " 18 0.000000 0.000000 0.000000 216\n", " 19 0.687078 0.915510 0.785014 6557\n", " 20 0.894879 0.952319 0.922706 11451\n", "\n", "avg / total 0.705082 0.808106 0.751003 20923\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 7, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.052392 0.065156 0.058081 353\n", " 11 0.118644 0.008347 0.015596 2516\n", " 12 0.080709 0.020961 0.033279 1956\n", " 13 0.123153 0.016319 0.028818 1532\n", " 14 0.023715 0.005141 0.008451 1167\n", " 15 0.087613 0.029774 0.044444 974\n", " 16 0.038674 0.009524 0.015284 735\n", " 17 0.035661 0.042032 0.038585 571\n", " 18 0.041009 0.031175 0.035422 417\n", " 19 0.429871 0.575645 0.492191 7555\n", " 20 0.325867 0.799809 0.463067 3147\n", "\n", "avg / total 0.244497 0.337189 0.260285 20923\n", "\n", "Classification report for turbine 7, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.034924 0.150754 0.056711 199\n", " 11 0.197452 0.417184 0.268041 966\n", " 12 0.072526 0.103155 0.085170 824\n", " 13 0.032222 0.039945 0.035670 726\n", " 14 0.031204 0.031297 0.031250 671\n", " 15 0.024221 0.022727 0.023451 616\n", " 16 0.041594 0.042781 0.042179 561\n", " 17 0.075908 0.048218 0.058974 477\n", " 18 0.043841 0.044872 0.044351 468\n", " 19 0.713929 0.635424 0.672393 11704\n", " 20 0.841997 0.663433 0.742125 3711\n", "\n", "avg / total 0.567664 0.504182 0.530419 20923\n", "\n", "Classification report for turbine 7, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.523677 0.140299 0.221307 1340\n", " 11 0.071918 0.258197 0.112500 488\n", " 12 0.031579 0.076923 0.044776 468\n", " 13 0.017654 0.035354 0.023549 396\n", " 14 0.015267 0.021978 0.018018 364\n", " 15 0.017327 0.019444 0.018325 360\n", " 16 0.028070 0.022222 0.024806 360\n", " 17 0.002809 0.002778 0.002793 360\n", " 18 0.049793 0.033333 0.039933 360\n", " 19 0.772918 0.687799 0.727879 15237\n", " 20 0.542384 0.688235 0.606667 1190\n", "\n", "avg / total 0.631928 0.559145 0.584611 20923\n", "\n", "Classification report for turbine 7, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.266667 0.115942 0.161616 414\n", " 11 0.009682 0.194444 0.018445 108\n", " 12 0.007392 0.064815 0.013270 108\n", " 13 0.001969 0.009259 0.003247 108\n", " 14 0.002825 0.009259 0.004329 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.004854 0.009259 0.006369 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.947414 0.754108 0.839781 18683\n", " 20 0.688377 0.714137 0.701020 962\n", "\n", "avg / total 0.883050 0.709984 0.785540 20923\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 7, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 19 0.886433 0.944939 0.914751 8318\n", " 20 0.962011 0.920111 0.940594 12605\n", "\n", "avg / total 0.931964 0.929981 0.930320 20923\n", "\n", "Classification report for turbine 7, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 2029\n", " 11 0.000000 0.000000 0.000000 120\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 96\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.924680 0.764717 0.837126 15203\n", " 20 0.328623 0.912537 0.483226 3007\n", "\n", "avg / total 0.719117 0.686804 0.677717 20923\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 7, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.098953 0.781955 0.175676 133\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.953918 0.968089 0.960951 16358\n", " 20 0.883608 0.708766 0.786588 3856\n", "\n", "avg / total 0.909265 0.892463 0.897371 20923\n", "\n", "Classification report for turbine 7, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.263415 0.545455 0.355263 99\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.125000 0.013889 0.025000 72\n", " 17 0.048780 0.027778 0.035398 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.958889 0.976910 0.967816 18623\n", " 20 0.825016 0.783385 0.803662 1625\n", "\n", "avg / total 0.919401 0.933088 0.925733 20923\n", "\n", "Classification report for turbine 7, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.515625 0.317308 0.392857 104\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.948920 0.985652 0.966937 18678\n", " 20 0.810953 0.846515 0.828352 1277\n", "\n", "avg / total 0.899161 0.933136 0.915696 20923\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 7, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.893063 0.931714 0.911979 8318\n", " 20 0.953614 0.926378 0.939799 12605\n", "\n", "avg / total 0.929542 0.928500 0.928739 20923\n", "\n", "Classification report for turbine 7, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.976614 0.753841 0.850888 16010\n", " 20 0.539872 0.941176 0.686155 4913\n", "\n", "avg / total 0.874061 0.797830 0.812207 20923\n", "\n", "Classification report for turbine 7, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.980629 0.984149 0.982386 16718\n", " 20 0.936068 0.922711 0.929341 4205\n", "\n", "avg / total 0.971674 0.971801 0.971725 20923\n", "\n", "Classification report for turbine 7, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.989048 0.989461 0.989254 19166\n", " 20 0.884505 0.880478 0.882487 1757\n", "\n", "avg / total 0.980269 0.980309 0.980288 20923\n", "\n", "Classification report for turbine 7, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.994102 0.993337 0.993719 19512\n", " 20 0.908836 0.918498 0.913641 1411\n", "\n", "avg / total 0.988352 0.988290 0.988319 20923\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 7, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 7\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.877586 0.927324 0.901770 8187\n", " 20 0.951271 0.938349 0.944766 12441\n", "\n", "avg / total 0.909027 0.920805 0.914621 20923\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 7, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.972085 0.761274 0.853860 16010\n", " 20 0.547365 0.927946 0.688567 4913\n", "\n", "avg / total 0.872355 0.800411 0.815047 20923\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 7, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 27\n", " 11 0.000000 0.000000 0.000000 144\n", " 12 0.000000 0.000000 0.000000 144\n", " 13 0.000000 0.000000 0.000000 144\n", " 14 0.000000 0.000000 0.000000 144\n", " 15 0.000000 0.000000 0.000000 144\n", " 16 0.000000 0.000000 0.000000 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.917376 0.982020 0.948598 15795\n", " 20 0.877951 0.885287 0.881604 3949\n", "\n", "avg / total 0.858242 0.908426 0.882501 20923\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 7, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 12\n", " 11 0.027027 0.013889 0.018349 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.026316 0.013889 0.018182 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.957872 0.975252 0.966484 18628\n", " 20 0.845690 0.821910 0.833630 1707\n", "\n", "avg / total 0.921984 0.935430 0.928610 20923\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 7, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 1.000000 0.153846 0.266667 13\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.962336 0.980263 0.971216 18949\n", " 20 0.876274 0.869314 0.872780 1385\n", "\n", "avg / total 0.930169 0.945419 0.937526 20923\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 7, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.891726 0.927747 0.909380 8318\n", " 20 0.951015 0.925664 0.938168 12605\n", "\n", "avg / total 0.927444 0.926492 0.926724 20923\n", "\n", "Classification 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'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 7, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.892309 0.930392 0.910953 8318\n", " 20 0.952735 0.925902 0.939127 12605\n", "\n", "avg / total 0.928712 0.927687 0.927926 20923\n", "\n", "Classification report for turbine 7, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.974204 0.766646 0.858052 16010\n", " 20 0.551177 0.933849 0.693208 4913\n", "\n", "avg / total 0.874872 0.805907 0.819344 20923\n", "\n", "Classification report for turbine 7, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.980913 0.983670 0.982290 16718\n", " 20 0.934343 0.923900 0.929092 4205\n", "\n", "avg / total 0.971553 0.971658 0.971598 20923\n", "\n", "Classification report for turbine 7, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 49\n", " 11 0.000000 0.000000 0.000000 136\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.948632 0.989706 0.968734 18361\n", " 20 0.830787 0.885938 0.857477 1657\n", "\n", "avg / total 0.898267 0.938680 0.918022 20923\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 7, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.991333 0.984830 0.988071 19512\n", " 20 0.901306 0.880227 0.890642 1411\n", "\n", "avg / total 0.985262 0.977776 0.981500 20923\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 8, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 446\n", " 11 0.000000 0.000000 0.000000 392\n", " 12 0.000000 0.000000 0.000000 360\n", " 13 0.050000 0.003058 0.005764 327\n", " 14 0.000000 0.000000 0.000000 290\n", " 15 0.051724 0.010714 0.017751 280\n", " 16 0.000000 0.000000 0.000000 252\n", " 17 0.000000 0.000000 0.000000 224\n", " 18 0.000000 0.000000 0.000000 216\n", " 19 0.793601 0.975462 0.875184 12511\n", " 20 0.568753 0.505918 0.535499 2281\n", "\n", "avg / total 0.640361 0.760111 0.692744 17579\n", "\n", "Classification report for turbine 8, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.970024 0.914220 0.941296 12672\n", " 20 0.949200 0.483595 0.640745 4907\n", "\n", "avg / total 0.964211 0.794016 0.857400 17579\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 8, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.021882 0.068027 0.033113 147\n", " 11 0.000000 0.000000 0.000000 86\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.918875 0.979754 0.948338 13237\n", " 20 0.922404 0.642996 0.757764 3605\n", "\n", "avg / total 0.881258 0.870186 0.869774 17579\n", "\n", "Classification report for turbine 8, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.146341 0.031250 0.051502 192\n", " 11 0.000000 0.000000 0.000000 301\n", " 12 0.115385 0.010417 0.019108 288\n", " 13 0.066667 0.007220 0.013029 277\n", " 14 0.000000 0.000000 0.000000 233\n", " 15 0.000000 0.000000 0.000000 216\n", " 16 0.000000 0.000000 0.000000 183\n", " 17 0.000000 0.000000 0.000000 180\n", " 18 0.000000 0.000000 0.000000 180\n", " 19 0.874181 0.983258 0.925517 13977\n", " 20 0.775238 0.786727 0.780940 1552\n", "\n", "avg / total 0.768041 0.851869 0.805903 17579\n", "\n", "Classification report for turbine 8, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.026316 0.142857 0.044444 7\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.060606 0.111111 0.078431 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.975484 0.981516 0.978490 15202\n", " 20 0.927100 0.842939 0.883019 2082\n", "\n", "avg / total 0.953518 0.948916 0.950941 17579\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 8, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 19 0.910144 0.989320 0.948082 14139\n", " 20 0.931674 0.598547 0.728850 3440\n", "\n", "avg / total 0.914357 0.912851 0.905181 17579\n", "\n", "Classification report for turbine 8, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 6\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.975967 0.974416 0.975191 12586\n", " 20 0.887493 0.946797 0.916186 4699\n", "\n", "avg / total 0.935994 0.950737 0.943109 17579\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 8, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 19 0.961133 0.989436 0.975079 13821\n", " 20 0.960684 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and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 8, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 19 0.991541 0.995849 0.993690 15419\n", " 20 0.969422 0.939352 0.954150 2160\n", "\n", "avg / total 0.988823 0.988907 0.988832 17579\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 8, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.911809 0.992291 0.950349 14139\n", " 20 0.950274 0.605523 0.739702 3440\n", "\n", "avg / total 0.919336 0.916605 0.909128 17579\n", "\n", "Classification report for turbine 8, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.984240 0.970881 0.977515 12672\n", " 20 0.927348 0.959853 0.943321 4907\n", "\n", "avg / total 0.968359 0.967802 0.967970 17579\n", "\n", "Classification report for turbine 8, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.968670 0.991028 0.979722 13821\n", " 20 0.963943 0.882118 0.921217 3758\n", "\n", "avg / total 0.967660 0.967746 0.967215 17579\n", "\n", "Classification report for turbine 8, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.985064 0.993807 0.989416 15662\n", " 20 0.945444 0.876891 0.909878 1917\n", "\n", "avg / total 0.980744 0.981057 0.980742 17579\n", "\n", "Classification report for turbine 8, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.990442 0.994682 0.992558 15419\n", " 20 0.960840 0.931481 0.945933 2160\n", "\n", "avg / total 0.986805 0.986916 0.986829 17579\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 8, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 19 0.903689 0.987481 0.943729 14139\n", " 20 0.916862 0.567442 0.701024 3440\n", "\n", "avg / total 0.906267 0.905285 0.896235 17579\n", "\n", "Classification report for turbine 8, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 6\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.961911 0.969357 0.965620 12401\n", " 20 0.921684 0.959050 0.939996 4884\n", "\n", "avg / total 0.934647 0.950282 0.942351 17579\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 8, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 123\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.947220 0.990689 0.968467 13532\n", " 20 0.933000 0.873212 0.902117 3636\n", "\n", "avg / total 0.922132 0.943228 0.932100 17579\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 8, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 43\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.142857 0.027778 0.046512 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.962756 0.983956 0.973240 15395\n", " 20 0.904903 0.826767 0.864072 1853\n", "\n", "avg / total 0.938822 0.948916 0.943503 17579\n", "\n", "Classification report for turbine 8, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.988289 0.990661 0.989474 15419\n", " 20 0.965703 0.912500 0.938348 2160\n", "\n", "avg / total 0.985514 0.981057 0.983192 17579\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 8, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 4\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 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"------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 8, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.555730 0.317489 0.404110 1115\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 64\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.898716 0.928382 0.913308 13572\n", " 20 0.888068 0.624201 0.733114 2504\n", "\n", "avg / total 0.855608 0.825815 0.835185 17579\n", "\n", "Classification report for turbine 8, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.008368 0.133333 0.015748 15\n", " 11 0.000000 0.000000 0.000000 46\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.952400 0.964026 0.958178 12370\n", " 20 0.929162 0.894812 0.911664 4896\n", "\n", "avg / total 0.928977 0.927698 0.928176 17579\n", "\n", "Classification report for turbine 8, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 290\n", " 11 0.000000 0.000000 0.000000 80\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 67\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.939978 0.967625 0.953601 13498\n", " 20 0.808976 0.649881 0.720753 3356\n", "\n", "avg / total 0.876202 0.867057 0.869820 17579\n", "\n", "Classification report for turbine 8, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.980311 0.985506 0.982902 15662\n", " 20 0.943834 0.806468 0.869761 1917\n", "\n", "avg / total 0.976333 0.965982 0.970564 17579\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 8, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.007407 0.011765 0.009091 85\n", " 11 0.058824 0.003968 0.007435 252\n", " 12 0.000000 0.000000 0.000000 252\n", " 13 0.000000 0.000000 0.000000 252\n", " 14 0.058824 0.003968 0.007435 252\n", " 15 0.000000 0.000000 0.000000 252\n", " 16 0.000000 0.000000 0.000000 252\n", " 17 0.000000 0.000000 0.000000 252\n", " 18 0.000000 0.000000 0.000000 252\n", " 19 0.885198 0.982043 0.931109 13811\n", " 20 0.737123 0.910018 0.814497 1667\n", "\n", "avg / total 0.767082 0.858012 0.809024 17579\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 8, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 19 0.918314 0.985925 0.950919 14139\n", " 20 0.917049 0.639535 0.753554 3440\n", "\n", "avg / total 0.918066 0.918141 0.912297 17579\n", "\n", "Classification report for turbine 8, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 19 0.982830 0.975694 0.979249 12672\n", " 20 0.938388 0.955981 0.947103 4907\n", "\n", "avg / total 0.970424 0.970192 0.970276 17579\n", "\n", "Classification report for turbine 8, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 19 0.971899 0.990956 0.981335 13821\n", " 20 0.964153 0.894625 0.928088 3758\n", "\n", "avg / total 0.970243 0.970362 0.969952 17579\n", "\n", "Classification report for turbine 8, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 125\n", " 11 0.000000 0.000000 0.000000 63\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.970275 0.994155 0.982070 15399\n", " 20 0.848418 0.878161 0.863033 1740\n", "\n", "avg / total 0.933928 0.957791 0.945707 17579\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 8, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 19 0.989429 0.995525 0.992468 15419\n", " 20 0.969906 0.910185 0.939097 2160\n", "\n", "avg / total 0.987030 0.985039 0.985910 17579\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 8, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.094595 0.009309 0.016949 752\n", " 11 0.000000 0.000000 0.000000 146\n", " 12 0.000000 0.000000 0.000000 111\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 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precision recall f1-score support\n", "\n", " 10 0.006550 0.428571 0.012903 14\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.933526 0.955813 0.944538 13488\n", " 20 0.918894 0.559840 0.695776 3501\n", "\n", "avg / total 0.899286 0.845213 0.863304 17579\n", "\n", "Classification report for turbine 8, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 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0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.964068 0.984227 0.974043 13821\n", " 20 0.962681 0.672698 0.791980 3758\n", "\n", "avg / total 0.963771 0.917629 0.935122 17579\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 8, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.978472 0.989593 0.984001 15662\n", " 20 0.944828 0.786124 0.858200 1917\n", "\n", "avg / total 0.974803 0.967404 0.970282 17579\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 8, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 5\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 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0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 65\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.972687 0.995704 0.984061 15129\n", " 20 0.888623 0.931363 0.909491 1996\n", "\n", "avg / total 0.938021 0.962683 0.950179 17579\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 8, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 30\n", " 11 0.000000 0.000000 0.000000 180\n", " 12 0.000000 0.000000 0.000000 180\n", " 13 0.000000 0.000000 0.000000 180\n", " 14 0.000000 0.000000 0.000000 180\n", " 15 0.000000 0.000000 0.000000 180\n", " 16 0.000000 0.000000 0.000000 180\n", " 17 0.000000 0.000000 0.000000 180\n", " 18 0.000000 0.000000 0.000000 180\n", " 19 0.833613 0.976397 0.899373 12710\n", " 20 0.877786 0.695204 0.775899 3399\n", "\n", "avg / total 0.772445 0.840378 0.800291 17579\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 8, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 24\n", " 11 0.000000 0.000000 0.000000 144\n", " 12 0.045455 0.013889 0.021277 144\n", " 13 0.000000 0.000000 0.000000 144\n", " 14 0.000000 0.000000 0.000000 144\n", " 15 0.000000 0.000000 0.000000 144\n", " 16 0.000000 0.000000 0.000000 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.909330 0.939608 0.924221 11773\n", " 20 0.883047 0.953996 0.917151 4630\n", "\n", "avg / total 0.841947 0.880653 0.860705 17579\n", "\n", "Classification report for turbine 8, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 7\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.018868 0.027778 0.022472 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.949014 0.958395 0.953681 13556\n", " 20 0.965755 0.862393 0.911152 3728\n", "\n", "avg / total 0.936677 0.922009 0.928704 17579\n", "\n", "Classification report for turbine 8, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.100000 0.052632 0.068966 19\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.029412 0.009259 0.014085 108\n", " 13 0.012500 0.009259 0.010638 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.045455 0.009259 0.015385 108\n", " 19 0.927280 0.975840 0.950940 14818\n", " 20 0.927553 0.831736 0.877035 1878\n", "\n", "avg / total 0.881376 0.911656 0.895600 17579\n", "\n", "Classification report for turbine 8, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.111111 0.052632 0.071429 19\n", " 11 0.085714 0.027778 0.041958 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.936440 0.983348 0.959321 14593\n", " 20 0.939483 0.915359 0.927264 2103\n", "\n", "avg / total 0.890413 0.926048 0.907634 17579\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 8, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.915119 0.989745 0.950970 14139\n", " 20 0.936598 0.622674 0.748036 3440\n", "\n", "avg / total 0.919322 0.917913 0.911258 17579\n", "\n", "Classification report for turbine 8, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.981493 0.970960 0.976198 12672\n", " 20 0.927028 0.952721 0.939698 4907\n", "\n", "avg / total 0.966290 0.965868 0.966010 17579\n", "\n", "Classification report for turbine 8, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.972960 0.991896 0.982337 13821\n", " 20 0.967899 0.898616 0.931972 3758\n", "\n", "avg / total 0.971878 0.971955 0.971570 17579\n", "\n", "Classification report for turbine 8, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.986247 0.993551 0.989885 15662\n", " 20 0.943920 0.886802 0.914470 1917\n", "\n", "avg / total 0.981631 0.981910 0.981661 17579\n", "\n", "Classification report for turbine 8, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.990961 0.995395 0.993173 15419\n", " 20 0.966045 0.935185 0.950365 2160\n", "\n", "avg / total 0.987899 0.987997 0.987913 17579\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 8, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.918839 0.984865 0.950707 14139\n", " 20 0.911716 0.642442 0.753752 3440\n", "\n", "avg / total 0.917445 0.917857 0.912165 17579\n", "\n", "Classification report for turbine 8, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.982453 0.972064 0.977231 12672\n", " 20 0.929776 0.955166 0.942300 4907\n", "\n", "avg / total 0.967749 0.967347 0.967481 17579\n", "\n", "Classification report for turbine 8, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.969057 0.992475 0.980626 13821\n", " 20 0.969626 0.883449 0.924534 3758\n", "\n", "avg / total 0.969179 0.969168 0.968635 17579\n", "\n", "Classification report for turbine 8, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 13\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 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0.000000 0.000000 0.000000 79\n", " 11 0.000000 0.000000 0.000000 55\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 46\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.928931 0.951594 0.940126 10288\n", " 20 0.947181 0.971539 0.959205 9838\n", "\n", "avg / total 0.914939 0.937857 0.926257 20630\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 9, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.061224 0.043269 0.050704 208\n", " 11 0.025000 0.005464 0.008969 183\n", " 12 0.000000 0.000000 0.000000 125\n", " 13 0.000000 0.000000 0.000000 58\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 26\n", " 16 0.000000 0.000000 0.000000 4\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.949552 0.980942 0.964992 16214\n", " 20 0.950593 0.929806 0.940085 3704\n", "\n", "avg / total 0.917806 0.938391 0.927806 20630\n", "\n", "Classification report for turbine 9, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.080000 0.033333 0.047059 60\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 32\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.973561 0.989165 0.981301 17720\n", " 20 0.939454 0.899924 0.919264 2638\n", "\n", "avg / total 0.956597 0.964809 0.960567 20630\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 9, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.240000 0.346154 0.283465 52\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.974854 0.990194 0.982464 17540\n", " 20 0.954156 0.930909 0.942389 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0.965171 0.964760 0.964774 20630\n", "\n", "Classification report for turbine 9, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 19 0.984915 0.989228 0.987067 16896\n", " 20 0.950273 0.931441 0.940763 3734\n", "\n", "avg / total 0.978645 0.978769 0.978686 20630\n", "\n", "Classification report for turbine 9, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 19 0.987420 0.993365 0.990384 17936\n", " 20 0.953983 0.915739 0.934470 2694\n", "\n", "avg / total 0.983053 0.983228 0.983082 20630\n", "\n", "Classification report for turbine 9, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 19 0.991881 0.993717 0.992798 17827\n", " 20 0.959567 0.948270 0.953885 2803\n", "\n", "avg / total 0.987491 0.987542 0.987511 20630\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 9, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.970824 0.991301 0.980956 17589\n", " 20 0.942697 0.827688 0.881457 3041\n", "\n", "avg / total 0.966678 0.967184 0.966289 20630\n", "\n", "Classification report for turbine 9, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 9\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.933033 0.951506 0.942179 10455\n", " 20 0.948435 0.957076 0.952736 9878\n", "\n", "avg / total 0.926975 0.940475 0.933670 20630\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no 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] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 9, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.982885 0.992585 0.987711 17936\n", " 20 0.955128 0.884929 0.918690 2694\n", "\n", "avg / total 0.979261 0.978526 0.978698 20630\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 9, turbine category 4.0\n", " precision recall 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0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 19 0.965779 0.991586 0.978512 17589\n", " 20 0.943501 0.785268 0.857143 3041\n", "\n", "avg / total 0.962495 0.961173 0.960621 20630\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 9, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.027027 0.019608 0.022727 102\n", " 11 0.000000 0.000000 0.000000 64\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 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0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.989434 0.987547 0.988490 17827\n", " 20 0.961278 0.912237 0.936116 2803\n", "\n", "avg / total 0.985609 0.977315 0.981374 20630\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 9, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.442849 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7358\n", " 20 0.573637 0.574377 0.574006 2326\n", "\n", "avg / total 0.670874 0.683325 0.671383 20630\n", "\n", "Classification report for turbine 9, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.091816 0.661871 0.161262 417\n", " 11 0.021505 0.011952 0.015365 502\n", " 12 0.051724 0.021635 0.030508 416\n", " 13 0.012285 0.014205 0.013175 352\n", " 14 0.032680 0.017361 0.022676 288\n", " 15 0.011494 0.003861 0.005780 259\n", " 16 0.023810 0.011905 0.015873 252\n", " 17 0.011765 0.004292 0.006289 233\n", " 18 0.000000 0.000000 0.000000 216\n", " 19 0.833794 0.866060 0.849621 14290\n", " 20 0.924133 0.375624 0.534141 3405\n", "\n", "avg / total 0.734738 0.676733 0.681804 20630\n", "\n", "Classification report for turbine 9, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.472042 0.802000 0.594294 1000\n", " 11 0.105128 0.040877 0.058866 1003\n", " 12 0.022222 0.004790 0.007882 835\n", " 13 0.018405 0.003947 0.006501 760\n", " 14 0.070866 0.012623 0.021429 713\n", " 15 0.296703 0.039474 0.069677 684\n", " 16 0.094891 0.019259 0.032020 675\n", " 17 0.011673 0.004894 0.006897 613\n", " 18 0.012987 0.001742 0.003072 574\n", " 19 0.684018 0.923183 0.785805 12341\n", " 20 0.645955 0.384777 0.482276 1432\n", "\n", "avg / total 0.499691 0.622734 0.540167 20630\n", "\n", "Classification report for turbine 9, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.534238 0.683535 0.599735 1324\n", " 11 0.111250 0.070973 0.086660 1254\n", " 12 0.047468 0.013636 0.021186 1100\n", " 13 0.081712 0.020448 0.032710 1027\n", " 14 0.034843 0.010846 0.016543 922\n", " 15 0.025532 0.006674 0.010582 899\n", " 16 0.036585 0.010883 0.016775 827\n", " 17 0.074890 0.021964 0.033966 774\n", " 18 0.022989 0.005626 0.009040 711\n", " 19 0.584307 0.863349 0.696935 10428\n", " 20 0.667343 0.482405 0.560000 1364\n", "\n", "avg / total 0.394863 0.520456 0.439285 20630\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 9, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.984186 0.990733 0.987449 17589\n", " 20 0.944254 0.907925 0.925733 3041\n", "\n", "avg / total 0.978300 0.978526 0.978351 20630\n", "\n", "Classification report for turbine 9, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.974049 0.953742 0.963789 10744\n", " 20 0.950841 0.972385 0.961492 9886\n", "\n", "avg / total 0.962928 0.962676 0.962688 20630\n", "\n", "Classification report for turbine 9, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.987140 0.985855 0.986497 16896\n", " 20 0.936368 0.941885 0.939119 3734\n", "\n", "avg / total 0.977950 0.977896 0.977922 20630\n", "\n", "Classification report for turbine 9, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.985843 0.993923 0.989866 17936\n", " 20 0.957205 0.904974 0.930357 2694\n", "\n", "avg / total 0.982103 0.982307 0.982095 20630\n", "\n", "Classification report for turbine 9, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 7\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.976109 0.994244 0.985093 17547\n", " 20 0.959013 0.948350 0.953652 2788\n", "\n", "avg / total 0.959841 0.973825 0.966758 20630\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 9, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 38\n", " 11 0.006173 0.004630 0.005291 216\n", " 12 0.010101 0.013889 0.011696 216\n", " 13 0.000000 0.000000 0.000000 216\n", " 14 0.000000 0.000000 0.000000 216\n", " 15 0.055556 0.023148 0.032680 216\n", " 16 0.000000 0.000000 0.000000 216\n", " 17 0.000000 0.000000 0.000000 216\n", " 18 0.000000 0.000000 0.000000 216\n", " 19 0.873698 0.937304 0.904384 15934\n", " 20 0.923643 0.813311 0.864973 2930\n", "\n", "avg / total 0.806752 0.839893 0.821888 20630\n", "\n", "Classification report for turbine 9, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.968326 0.930473 0.949022 10744\n", " 20 0.952396 0.936982 0.944626 9886\n", "\n", "avg / total 0.960692 0.933592 0.946915 20630\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 9, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 18\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.936020 0.966621 0.951074 16028\n", " 20 0.946800 0.942473 0.944632 3720\n", "\n", "avg / total 0.897946 0.920940 0.909251 20630\n", "\n", "Classification report for turbine 9, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 12\n", " 11 0.025000 0.027778 0.026316 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.951551 0.980029 0.965580 17375\n", " 20 0.951792 0.866142 0.906949 2667\n", "\n", "avg / total 0.924548 0.937470 0.930571 20630\n", "\n", "Classification report for turbine 9, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 12\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.957994 0.980758 0.969242 17254\n", " 20 0.959618 0.937590 0.948476 2788\n", "\n", "avg / total 0.930908 0.946970 0.938810 20630\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 9, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.983308 0.991358 0.987317 17589\n", " 20 0.947532 0.902664 0.924554 3041\n", "\n", "avg / total 0.978034 0.978284 0.978065 20630\n", "\n", "Classification report for turbine 9, turbine category 19.0\n", " precision recall 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"------------------------------------------------------------------------\n", "Classification report for turbine 9, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.981169 0.989425 0.985280 17589\n", " 20 0.935707 0.890168 0.912369 3041\n", "\n", "avg / total 0.974468 0.974794 0.974532 20630\n", "\n", "Classification report for turbine 9, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.958524 0.952904 0.955706 10744\n", " 20 0.949141 0.955189 0.952155 9886\n", "\n", "avg / total 0.954028 0.953999 0.954004 20630\n", "\n", "Classification report for turbine 9, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.988152 0.987216 0.987684 16896\n", " 20 0.942400 0.946438 0.944415 3734\n", "\n", "avg / total 0.979871 0.979835 0.979852 20630\n", "\n", "Classification report for turbine 9, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 316\n", " 11 0.000000 0.000000 0.000000 432\n", " 12 0.000000 0.000000 0.000000 432\n", " 13 0.000000 0.000000 0.000000 424\n", " 14 0.000000 0.000000 0.000000 339\n", " 15 0.000000 0.000000 0.000000 288\n", " 16 0.000000 0.000000 0.000000 288\n", " 17 0.000000 0.000000 0.000000 280\n", " 18 0.000000 0.000000 0.000000 229\n", " 19 0.846209 0.994213 0.914260 15380\n", " 20 0.789844 0.909991 0.845671 2222\n", "\n", "avg / total 0.715935 0.839215 0.772681 20630\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 9, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.989616 0.983620 0.986609 17827\n", " 20 0.960571 0.912594 0.935968 2803\n", "\n", "avg / total 0.985669 0.973970 0.979728 20630\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 10, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.976257 0.793363 0.875359 19798\n", " 20 0.716870 0.716170 0.716520 2047\n", "\n", "avg / total 0.951951 0.786130 0.860475 21845\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 10, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.985300 0.967470 0.976303 18844\n", " 20 0.922235 0.814062 0.864779 3001\n", "\n", "avg / total 0.976636 0.946395 0.960982 21845\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 10, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.360000 0.062937 0.107143 143\n", " 11 0.076923 0.013889 0.023529 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 38\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.966195 0.966601 0.966398 14282\n", " 20 0.927870 0.964154 0.945664 7058\n", "\n", "avg / total 0.934087 0.943923 0.938138 21845\n", "\n", "Classification report for turbine 10, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.996627 0.988689 0.992642 21219\n", " 20 0.787572 0.870607 0.827011 626\n", "\n", "avg / total 0.990636 0.985306 0.987896 21845\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 10, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 19 0.998252 0.995713 0.996981 21225\n", " 20 0.910798 0.938710 0.924543 620\n", "\n", "avg / total 0.995770 0.994095 0.994925 21845\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 10, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 9\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.969209 0.964837 0.967018 19509\n", " 20 0.712459 0.846984 0.773919 2039\n", "\n", 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21845\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 10, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 7\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.960784 0.940657 0.950614 14273\n", " 20 0.948070 0.958362 0.953188 7277\n", "\n", "avg / total 0.943574 0.933852 0.938634 21845\n", "\n" ] }, { 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precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.996724 0.989443 0.993071 21219\n", " 20 0.786119 0.886581 0.833333 626\n", "\n", "avg / total 0.990689 0.986496 0.988493 21845\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 10, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 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0.000000 0.000000 0.000000 36\n", " 14 0.058824 0.027778 0.037736 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.948864 0.936095 0.942437 14193\n", " 20 0.866058 0.939790 0.901419 6660\n", "\n", "avg / total 0.880627 0.894759 0.887197 21845\n", "\n", "Classification report for turbine 10, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 10\n", " 11 0.000000 0.000000 0.000000 56\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 43\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.981862 0.988716 0.985277 20915\n", " 20 0.724963 0.852373 0.783522 569\n", "\n", "avg / total 0.958945 0.968826 0.963740 21845\n", "\n", "Classification report for turbine 10, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 85\n", " 11 0.016949 0.005556 0.008368 180\n", " 12 0.000000 0.000000 0.000000 180\n", " 13 0.000000 0.000000 0.000000 180\n", " 14 0.000000 0.000000 0.000000 180\n", " 15 0.000000 0.000000 0.000000 180\n", " 16 0.000000 0.000000 0.000000 180\n", " 17 0.076923 0.017341 0.028302 173\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.937649 0.990213 0.963214 19925\n", " 20 0.569260 0.684932 0.621762 438\n", "\n", "avg / total 0.867399 0.917098 0.891315 21845\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 10, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 19 0.980430 0.964138 0.972216 19798\n", " 20 0.701178 0.813874 0.753335 2047\n", "\n", "avg / total 0.954263 0.950057 0.951705 21845\n", "\n", "Classification report for turbine 10, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 63\n", " 11 0.000000 0.000000 0.000000 99\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 51\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.966714 0.991439 0.978920 18455\n", " 20 0.921179 0.918974 0.920075 2925\n", "\n", "avg / total 0.940039 0.960632 0.950203 21845\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 10, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 19 0.978298 0.972051 0.975164 14562\n", " 20 0.952107 0.955376 0.953739 7283\n", "\n", "avg / total 0.969566 0.966491 0.968021 21845\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 10, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 19 0.994607 0.990904 0.992752 21219\n", " 20 0.817590 0.801917 0.809677 626\n", "\n", "avg / total 0.989535 0.985489 0.987506 21845\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 10, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.997923 0.995807 0.996864 21225\n", " 20 0.911392 0.929032 0.920128 620\n", "\n", "avg / total 0.995467 0.993912 0.994686 21845\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 10, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.088608 0.220721 0.126452 222\n", " 11 0.093633 0.135624 0.110783 553\n", " 12 0.059783 0.061111 0.060440 540\n", " 13 0.032590 0.035316 0.033898 538\n", " 14 0.017857 0.019841 0.018797 504\n", " 15 0.004864 0.009921 0.006527 504\n", " 16 0.015228 0.012579 0.013777 477\n", " 17 0.016878 0.008547 0.011348 468\n", " 18 0.019231 0.010684 0.013736 468\n", " 19 0.800182 0.778753 0.789322 15833\n", " 20 0.628065 0.530495 0.575172 1738\n", "\n", "avg / total 0.637113 0.616068 0.625693 21845\n", "\n", "Classification report for turbine 10, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.037143 0.089655 0.052525 145\n", " 11 0.063492 0.062500 0.062992 256\n", " 12 0.019512 0.015873 0.017505 252\n", " 13 0.004926 0.003968 0.004396 252\n", " 14 0.010000 0.003968 0.005682 252\n", " 15 0.013699 0.015873 0.014706 252\n", " 16 0.000000 0.000000 0.000000 252\n", " 17 0.068376 0.032520 0.044077 246\n", " 18 0.010204 0.004630 0.006369 216\n", " 19 0.893263 0.921927 0.907368 16984\n", " 20 0.829586 0.768079 0.797648 2738\n", "\n", "avg / total 0.800887 0.815244 0.807568 21845\n", "\n", "Classification report for turbine 10, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.101173 0.450980 0.165269 153\n", " 11 0.000000 0.000000 0.000000 116\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.026316 0.009259 0.013699 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.012821 0.018519 0.015152 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.922482 0.906300 0.914319 13682\n", " 20 0.940178 0.900532 0.919928 7138\n", "\n", "avg / total 0.885882 0.865187 0.874551 21845\n", "\n", "Classification report for turbine 10, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.750000 0.736364 0.743119 110\n", " 11 0.046875 0.020833 0.028846 144\n", " 12 0.015873 0.008065 0.010695 124\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 84\n", " 18 0.020408 0.027778 0.023529 72\n", " 19 0.956267 0.968190 0.962191 20371\n", " 20 0.735612 0.805118 0.768797 508\n", "\n", "avg / total 0.913092 0.925566 0.919216 21845\n", "\n", "Classification report for turbine 10, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.014706 0.021739 0.017544 46\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.973722 0.977061 0.975389 20707\n", " 20 0.747126 0.881783 0.808889 516\n", "\n", "avg / total 0.940676 0.947036 0.943720 21845\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 10, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.763833 0.748677 0.756179 756\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.038095 0.055556 0.045198 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.005435 0.013889 0.007812 72\n", " 16 0.005128 0.013889 0.007491 72\n", " 17 0.017699 0.055556 0.026846 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.951906 0.889543 0.919668 19202\n", " 20 0.658706 0.652174 0.655424 1311\n", "\n", "avg / total 0.902920 0.847425 0.874191 21845\n", "\n", "Classification report for turbine 10, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.710871 0.513649 0.596378 1795\n", " 11 0.173077 0.132743 0.150250 339\n", " 12 0.019391 0.023810 0.021374 294\n", " 13 0.000000 0.000000 0.000000 288\n", " 14 0.031746 0.006944 0.011396 288\n", " 15 0.049383 0.013889 0.021680 288\n", " 16 0.000000 0.000000 0.000000 288\n", " 17 0.000000 0.000000 0.000000 288\n", " 18 0.000000 0.000000 0.000000 288\n", " 19 0.872358 0.957007 0.912724 16561\n", " 20 0.509030 0.674645 0.580252 1128\n", "\n", "avg / total 0.750060 0.805219 0.773971 21845\n", "\n", "Classification report for turbine 10, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.007567 0.383721 0.014841 86\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.946916 0.916055 0.931230 14176\n", " 20 0.848754 0.354788 0.500403 7007\n", "\n", "avg / total 0.886763 0.709773 0.764876 21845\n", "\n", "Classification report for turbine 10, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.995005 0.976248 0.985537 21219\n", " 20 0.758564 0.742812 0.750605 626\n", "\n", "avg / total 0.988229 0.969558 0.978805 21845\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 10, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 5\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.983972 0.991163 0.987554 20935\n", " 20 0.898687 0.776337 0.833043 617\n", "\n", "avg / total 0.968365 0.971801 0.969945 21845\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 10, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 19 0.978447 0.972219 0.975323 19798\n", " 20 0.769450 0.792379 0.780746 2047\n", "\n", "avg / total 0.958862 0.955367 0.957090 21845\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program 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"Classification report for turbine 10, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 13 0.000000 0.000000 0.000000 0\n", " 19 0.978240 0.975553 0.976895 14562\n", " 20 0.951516 0.956611 0.954057 7283\n", "\n", "avg / total 0.969330 0.969238 0.969281 21845\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 10, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 19 0.996357 0.992507 0.994428 21219\n", " 20 0.782051 0.876997 0.826807 626\n", "\n", "avg / total 0.990216 0.989197 0.989625 21845\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 10, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 19 0.998113 0.996985 0.997549 21225\n", " 20 0.907668 0.935484 0.921366 620\n", "\n", "avg / total 0.995546 0.995239 0.995386 21845\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 10, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 62\n", " 11 0.000000 0.000000 0.000000 360\n", " 12 0.000000 0.000000 0.000000 360\n", " 13 0.000000 0.000000 0.000000 360\n", " 14 0.047619 0.002778 0.005249 360\n", " 15 0.000000 0.000000 0.000000 360\n", " 16 0.021277 0.002959 0.005195 338\n", " 17 0.000000 0.000000 0.000000 324\n", " 18 0.035714 0.006173 0.010526 324\n", " 19 0.855770 0.969385 0.909041 17181\n", " 20 0.673007 0.818282 0.738569 1816\n", "\n", "avg / total 0.730651 0.830625 0.776678 21845\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 10, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 11\n", " 11 0.005747 0.013889 0.008130 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.003745 0.013889 0.005900 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.956084 0.913312 0.934209 18307\n", " 20 0.912268 0.849204 0.879607 2951\n", "\n", "avg / total 0.924505 0.880201 0.901776 21845\n", "\n", "Classification report for turbine 10, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.066667 0.083333 0.074074 24\n", " 11 0.050847 0.020833 0.029557 144\n", " 12 0.020000 0.006944 0.010309 144\n", " 13 0.000000 0.000000 0.000000 144\n", " 14 0.020408 0.020833 0.020619 144\n", " 15 0.000000 0.000000 0.000000 144\n", " 16 0.000000 0.000000 0.000000 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.903325 0.907121 0.905219 13566\n", " 20 0.933957 0.913839 0.923789 7103\n", "\n", "avg / total 0.865331 0.860883 0.863006 21845\n", "\n", "Classification report for turbine 10, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 17\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.035714 0.018519 0.024390 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.956228 0.972532 0.964311 20351\n", " 20 0.778426 0.871126 0.822171 613\n", "\n", "avg / total 0.912851 0.930556 0.921553 21845\n", "\n", "Classification report for turbine 10, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.090909 0.041667 0.057143 24\n", " 11 0.034188 0.027778 0.030651 144\n", " 12 0.000000 0.000000 0.000000 144\n", " 13 0.000000 0.000000 0.000000 144\n", " 14 0.024390 0.006944 0.010811 144\n", " 15 0.000000 0.000000 0.000000 144\n", " 16 0.019608 0.006944 0.010256 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.023256 0.006944 0.010695 144\n", " 19 0.944353 0.972082 0.958017 20059\n", " 20 0.884311 0.914754 0.899275 610\n", "\n", "avg / total 0.892607 0.918517 0.905277 21845\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 10, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.981620 0.963027 0.972234 19798\n", " 20 0.697770 0.825598 0.756321 2047\n", "\n", "avg / total 0.955021 0.950149 0.952002 21845\n", "\n", "Classification report for turbine 10, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.987937 0.990925 0.989429 18844\n", " 20 0.941916 0.924025 0.932885 3001\n", "\n", "avg / total 0.981615 0.981735 0.981661 21845\n", "\n", "Classification report for turbine 10, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.983210 0.973149 0.978154 14562\n", " 20 0.947390 0.966772 0.956983 7283\n", "\n", "avg / total 0.971267 0.971023 0.971095 21845\n", "\n", "Classification report for turbine 10, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.996596 0.993402 0.994996 21219\n", " 20 0.798271 0.884984 0.839394 626\n", "\n", "avg / total 0.990913 0.990295 0.990537 21845\n", "\n", "Classification report for turbine 10, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.998302 0.997032 0.997666 21225\n", " 20 0.902628 0.941935 0.921863 620\n", "\n", "avg / total 0.995586 0.995468 0.995515 21845\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 10, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.980608 0.968027 0.974277 19798\n", " 20 0.724902 0.814851 0.767249 2047\n", "\n", "avg / total 0.956647 0.953674 0.954877 21845\n", "\n", "Classification report for turbine 10, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.987939 0.991085 0.989509 18844\n", " 20 0.942877 0.924025 0.933356 3001\n", "\n", "avg / total 0.981749 0.981872 0.981795 21845\n", "\n", "Classification report for turbine 10, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.982810 0.977613 0.980204 14562\n", " 20 0.955707 0.965811 0.960732 7283\n", "\n", "avg / total 0.973774 0.973678 0.973713 21845\n", "\n", "Classification report for turbine 10, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 13\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.984578 0.993128 0.988835 20956\n", " 20 0.743989 0.894558 0.812355 588\n", "\n", "avg / total 0.964535 0.976791 0.970459 21845\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 10, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 6\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.125000 0.027778 0.045455 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.988381 0.995339 0.991848 21024\n", " 20 0.760766 0.905123 0.826690 527\n", "\n", "avg / total 0.969794 0.979812 0.974589 21845\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 11, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 4\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.977823 0.991798 0.984761 16582\n", " 20 0.901956 0.914569 0.908219 3933\n", "\n", "avg / total 0.949760 0.963282 0.956473 20807\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 11, turbine category 2.0\n", " precision recall f1-score 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0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.964191 0.988563 0.976225 18712\n", " 20 0.849718 0.755989 0.800118 1795\n", "\n", "avg / total 0.940413 0.954246 0.946957 20807\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 11, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.989373 0.993325 0.991345 19027\n", " 20 0.943577 0.883146 0.912362 1780\n", "\n", "avg / total 0.985456 0.983900 0.984589 20807\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 11, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 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0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.974003 0.985044 0.979492 18789\n", " 20 0.877719 0.739841 0.802904 2018\n", "\n", "avg / total 0.964665 0.961263 0.962366 20807\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 11, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 4\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.910769 0.956798 0.933216 13356\n", " 20 0.950428 0.838246 0.890819 7159\n", "\n", "avg / total 0.911633 0.902581 0.905532 20807\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 11, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.974839 0.984998 0.979892 18998\n", " 20 0.861039 0.733002 0.791878 1809\n", "\n", "avg / total 0.964945 0.963089 0.963546 20807\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 11, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.988804 0.993325 0.991059 19027\n", " 20 0.942598 0.876404 0.908297 1780\n", "\n", "avg / total 0.984851 0.983323 0.983979 20807\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 11, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.972409 0.990631 0.981435 16650\n", " 20 0.959428 0.887419 0.922019 4157\n", "\n", "avg / total 0.969815 0.970010 0.969565 20807\n", "\n", "Classification report for turbine 11, 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"------------------------------------------------------------------------\n", "Classification report for turbine 11, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.968718 0.952252 0.960414 16650\n", " 20 0.959459 0.853981 0.903653 4157\n", "\n", "avg / total 0.966868 0.932619 0.949074 20807\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": 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0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.975227 0.978050 0.976637 18998\n", " 20 0.861886 0.717523 0.783107 1809\n", "\n", "avg / total 0.965373 0.955400 0.959811 20807\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 11, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 31\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.979582 0.989555 0.984543 18860\n", " 20 0.855569 0.858722 0.857143 1628\n", "\n", "avg / total 0.954861 0.964147 0.959481 20807\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 11, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 19 0.975222 0.990450 0.982777 16650\n", " 20 0.959199 0.899206 0.928234 4157\n", "\n", "avg / total 0.972021 0.972221 0.971880 20807\n", "\n", "Classification report for turbine 11, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 19 0.979177 0.988557 0.983844 18789\n", " 20 0.883025 0.804262 0.841805 2018\n", "\n", "avg / total 0.969851 0.970683 0.970069 20807\n", "\n", "Classification report for turbine 11, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 269\n", " 11 0.000000 0.000000 0.000000 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12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.958838 0.985363 0.971920 18652\n", " 20 0.827428 0.715258 0.767265 1763\n", "\n", "avg / total 0.929639 0.943913 0.936268 20807\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 11, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.988245 0.994114 0.991170 19027\n", " 20 0.951265 0.866292 0.906792 1780\n", "\n", "avg / total 0.985081 0.983179 0.983952 20807\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 11, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 19 0.978327 0.989550 0.983906 16650\n", " 20 0.956127 0.912196 0.933645 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0.000000 0.000000 720\n", " 12 0.000000 0.000000 0.000000 300\n", " 13 0.000000 0.000000 0.000000 159\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.894784 0.996794 0.943038 17157\n", " 20 0.402597 0.848259 0.546037 804\n", "\n", "avg / total 0.753376 0.854712 0.798708 20807\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 11, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 1111\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.905438 0.989804 0.945743 15594\n", " 20 0.739909 0.854849 0.793237 3238\n", "\n", "avg / total 0.793734 0.874850 0.832240 20807\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 11, turbine category 8.0\n", " precision 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" 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.942568 0.953323 0.947915 13497\n", " 20 0.972267 0.820109 0.889730 7310\n", "\n", "avg / total 0.953002 0.906522 0.927473 20807\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 11, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 91\n", " 11 0.250000 0.004425 0.008696 226\n", " 12 0.000000 0.000000 0.000000 216\n", " 13 0.000000 0.000000 0.000000 216\n", " 14 0.000000 0.000000 0.000000 181\n", " 15 0.000000 0.000000 0.000000 147\n", " 16 0.000000 0.000000 0.000000 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.500000 0.006944 0.013699 144\n", " 19 0.903604 0.984901 0.942503 17617\n", " 20 0.789330 0.686496 0.734330 1681\n", "\n", "avg / total 0.835015 0.889460 0.857520 20807\n", "\n", "Classification report for turbine 11, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.083333 0.200000 0.117647 20\n", " 11 0.000000 0.000000 0.000000 180\n", " 12 0.000000 0.000000 0.000000 180\n", " 13 0.000000 0.000000 0.000000 180\n", " 14 0.000000 0.000000 0.000000 180\n", " 15 0.000000 0.000000 0.000000 180\n", " 16 0.000000 0.000000 0.000000 180\n", " 17 0.000000 0.000000 0.000000 180\n", " 18 0.000000 0.000000 0.000000 180\n", " 19 0.920721 0.991530 0.954815 17710\n", " 20 0.872458 0.864997 0.868712 1637\n", "\n", "avg / total 0.852399 0.912193 0.881156 20807\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 11, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 47\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.949218 0.937561 0.943353 16368\n", " 20 0.942783 0.798977 0.864943 4104\n", "\n", "avg / total 0.932666 0.895131 0.912699 20807\n", "\n", "Classification report for turbine 11, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.972943 0.976050 0.974494 18789\n", " 20 0.878450 0.741328 0.804085 2018\n", "\n", "avg / total 0.963778 0.953285 0.957966 20807\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 11, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.937373 0.953693 0.945463 13497\n", " 20 0.968977 0.875923 0.920103 7310\n", "\n", "avg / total 0.948476 0.926371 0.936553 20807\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 11, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.974909 0.985788 0.980318 18998\n", " 20 0.872497 0.722499 0.790445 1809\n", "\n", "avg / total 0.966005 0.962897 0.963810 20807\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 11, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.989514 0.991906 0.990709 19027\n", " 20 0.944345 0.886517 0.914518 1780\n", "\n", "avg / total 0.985650 0.982890 0.984191 20807\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 11, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.071795 0.308824 0.116505 136\n", " 11 0.004902 0.011111 0.006803 180\n", " 12 0.042781 0.044444 0.043597 180\n", " 13 0.000000 0.000000 0.000000 180\n", " 14 0.011628 0.006173 0.008065 162\n", " 15 0.000000 0.000000 0.000000 144\n", " 16 0.009091 0.013889 0.010989 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.894307 0.901849 0.898062 15415\n", " 20 0.930810 0.754148 0.833218 3978\n", "\n", "avg / total 0.841546 0.814966 0.825971 20807\n", "\n", "Classification report for turbine 11, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 4\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.971104 0.942709 0.956696 18502\n", " 20 0.869901 0.783905 0.824667 2013\n", "\n", "avg / total 0.947685 0.914115 0.930496 20807\n", "\n", "Classification report for turbine 11, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.242718 0.332447 0.280584 376\n", " 11 0.041667 0.010929 0.017316 183\n", " 12 0.037500 0.019481 0.025641 154\n", " 13 0.000000 0.000000 0.000000 144\n", " 14 0.030303 0.006944 0.011299 144\n", " 15 0.000000 0.000000 0.000000 144\n", " 16 0.000000 0.000000 0.000000 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.000000 0.000000 0.000000 169\n", " 19 0.863515 0.933867 0.897314 12127\n", " 20 0.940859 0.910285 0.925320 7078\n", "\n", "avg / total 0.828580 0.860239 0.843244 20807\n", "\n", "Classification report for turbine 11, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.187291 0.282828 0.225352 198\n", " 11 0.027778 0.003472 0.006173 288\n", " 12 0.000000 0.000000 0.000000 288\n", " 13 0.000000 0.000000 0.000000 288\n", " 14 0.000000 0.000000 0.000000 288\n", " 15 0.000000 0.000000 0.000000 288\n", " 16 0.000000 0.000000 0.000000 288\n", " 17 0.000000 0.000000 0.000000 288\n", " 18 0.000000 0.000000 0.000000 263\n", " 19 0.861352 0.961961 0.908881 16746\n", " 20 0.796309 0.708333 0.749749 1584\n", "\n", "avg / total 0.756026 0.830874 0.790797 20807\n", "\n", "Classification report for turbine 11, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.312217 0.193277 0.238754 357\n", " 11 0.000000 0.000000 0.000000 187\n", " 12 0.000000 0.000000 0.000000 180\n", " 13 0.025000 0.005556 0.009091 180\n", " 14 0.000000 0.000000 0.000000 180\n", " 15 0.000000 0.000000 0.000000 167\n", " 16 0.000000 0.000000 0.000000 144\n", " 17 0.034483 0.006944 0.011561 144\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.916924 0.979799 0.947319 17573\n", " 20 0.818787 0.792392 0.805374 1551\n", "\n", "avg / total 0.841254 0.889989 0.864368 20807\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 11, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.576543 0.341250 0.428735 2737\n", " 11 0.102041 0.099206 0.100604 252\n", " 12 0.000000 0.000000 0.000000 252\n", " 13 0.031915 0.011905 0.017341 252\n", " 14 0.012346 0.003968 0.006006 252\n", " 15 0.019231 0.003968 0.006579 252\n", " 16 0.000000 0.000000 0.000000 252\n", " 17 0.021277 0.007937 0.011561 252\n", " 18 0.014388 0.007937 0.010230 252\n", " 19 0.860309 0.943937 0.900185 14680\n", " 20 0.279617 0.467249 0.349864 1374\n", "\n", "avg / total 0.703717 0.743356 0.716454 20807\n", "\n", "Classification report for turbine 11, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.752825 0.294313 0.423184 1811\n", " 11 0.124060 0.320388 0.178862 103\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.062500 0.041667 0.050000 72\n", " 14 0.041667 0.013889 0.020833 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.014706 0.013889 0.014286 72\n", " 18 0.022222 0.013889 0.017094 72\n", " 19 0.936361 0.968682 0.952247 17817\n", " 20 0.380465 0.715035 0.496661 572\n", "\n", "avg / total 0.878890 0.876628 0.867133 20807\n", "\n", "Classification report for turbine 11, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.001926 0.137500 0.003798 80\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.888740 0.895008 0.891863 12620\n", " 20 0.895942 0.189010 0.312165 7243\n", "\n", "avg / total 0.850933 0.609170 0.649619 20807\n", "\n", "Classification report for turbine 11, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.388235 0.242902 0.298836 951\n", " 11 0.000000 0.000000 0.000000 319\n", " 12 0.000000 0.000000 0.000000 288\n", " 13 0.000000 0.000000 0.000000 288\n", " 14 0.000000 0.000000 0.000000 288\n", " 15 0.000000 0.000000 0.000000 231\n", " 16 0.000000 0.000000 0.000000 216\n", " 17 0.000000 0.000000 0.000000 216\n", " 18 0.016667 0.004630 0.007246 216\n", " 19 0.876435 0.966797 0.919401 16896\n", " 20 0.539982 0.669265 0.597713 898\n", "\n", "avg / total 0.752918 0.825107 0.786116 20807\n", "\n", "Classification report for turbine 11, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.100213 0.305195 0.150883 154\n", " 11 0.000000 0.000000 0.000000 324\n", " 12 0.000000 0.000000 0.000000 324\n", " 13 0.025000 0.003086 0.005495 324\n", " 14 0.000000 0.000000 0.000000 324\n", " 15 0.000000 0.000000 0.000000 324\n", " 16 0.000000 0.000000 0.000000 324\n", " 17 0.000000 0.000000 0.000000 324\n", " 18 0.055556 0.003086 0.005848 324\n", " 19 0.857128 0.971366 0.910678 16484\n", " 20 0.867395 0.705136 0.777894 1577\n", "\n", "avg / total 0.746783 0.825347 0.781721 20807\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 11, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.973220 0.973453 0.973337 16650\n", " 20 0.968359 0.876113 0.919929 4157\n", "\n", "avg / total 0.972249 0.954006 0.962666 20807\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 11, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 6\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.966890 0.985862 0.976284 18602\n", " 20 0.814794 0.755102 0.783813 1911\n", "\n", "avg / total 0.939259 0.950738 0.944812 20807\n", "\n", "Classification report for turbine 11, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.913013 0.951841 0.932023 13497\n", " 20 0.964348 0.828865 0.891488 7310\n", "\n", "avg / total 0.931048 0.908637 0.917782 20807\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 11, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.975570 0.981630 0.978591 18998\n", " 20 0.843586 0.712548 0.772550 1809\n", "\n", "avg / total 0.964095 0.958235 0.960677 20807\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 11, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 13\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.975441 0.993440 0.984358 18751\n", " 20 0.930012 0.893447 0.911363 1755\n", "\n", "avg / total 0.957498 0.970635 0.963962 20807\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 11, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 49\n", " 11 0.000000 0.000000 0.000000 288\n", " 12 0.000000 0.000000 0.000000 288\n", " 13 0.000000 0.000000 0.000000 288\n", " 14 0.055556 0.007326 0.012945 273\n", " 15 0.075000 0.011905 0.020548 252\n", " 16 0.000000 0.000000 0.000000 252\n", " 17 0.042553 0.007937 0.013378 252\n", " 18 0.027778 0.017699 0.021622 226\n", " 19 0.864637 0.973972 0.916054 14638\n", " 20 0.929941 0.909023 0.919363 4001\n", "\n", "avg / total 0.789557 0.860528 0.822057 20807\n", "\n", "Classification report for turbine 11, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.032787 0.166667 0.054795 12\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.010753 0.013889 0.012121 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.946797 0.954466 0.950616 18272\n", " 20 0.814164 0.738059 0.774246 1947\n", "\n", "avg / total 0.907686 0.907387 0.907322 20807\n", "\n", "Classification report for turbine 11, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.200000 0.076923 0.111111 13\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.034483 0.013889 0.019802 72\n", " 14 0.028571 0.013889 0.018692 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.906405 0.958701 0.931820 12930\n", " 20 0.962821 0.899012 0.929823 7288\n", "\n", "avg / total 0.900851 0.910799 0.904945 20807\n", "\n", "Classification report for turbine 11, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 13\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.052632 0.027778 0.036364 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.057143 0.055556 0.056338 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.029412 0.013889 0.018868 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.952923 0.973100 0.962906 18513\n", " 20 0.785938 0.734311 0.759248 1705\n", "\n", "avg / total 0.912746 0.926323 0.919345 20807\n", "\n", "Classification report for turbine 11, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 19\n", " 11 0.037037 0.009259 0.014815 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.947604 0.986825 0.966817 18217\n", " 20 0.901257 0.882250 0.891652 1707\n", "\n", "avg / total 0.903780 0.936416 0.919698 20807\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 11, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.975231 0.988468 0.981805 16650\n", " 20 0.951157 0.899447 0.924580 4157\n", "\n", "avg / total 0.970421 0.970683 0.970372 20807\n", "\n", "Classification report for turbine 11, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.972952 0.987865 0.980352 18789\n", " 20 0.868208 0.744301 0.801494 2018\n", "\n", "avg / total 0.962793 0.964243 0.963005 20807\n", "\n", "Classification report for turbine 11, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.959263 0.983996 0.971472 13497\n", " 20 0.968974 0.922845 0.945348 7310\n", "\n", "avg / total 0.962675 0.962513 0.962294 20807\n", "\n", "Classification report for turbine 11, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.978074 0.988525 0.983272 18998\n", " 20 0.864259 0.767275 0.812884 1809\n", "\n", "avg / total 0.968179 0.969289 0.968458 20807\n", "\n", "Classification report for turbine 11, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 66\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 68\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.967130 0.995696 0.981205 18587\n", " 20 0.921005 0.891657 0.906094 1726\n", "\n", "avg / total 0.940342 0.963426 0.951679 20807\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 11, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.974236 0.990210 0.982158 16650\n", " 20 0.958033 0.895117 0.925507 4157\n", "\n", "avg / total 0.970999 0.971212 0.970840 20807\n", "\n", "Classification report for turbine 11, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.976814 0.986588 0.981677 18789\n", " 20 0.862295 0.781962 0.820166 2018\n", "\n", "avg / total 0.965707 0.966742 0.966012 20807\n", "\n", "Classification report for turbine 11, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.956741 0.983181 0.969781 13497\n", " 20 0.967277 0.917921 0.941953 7310\n", "\n", "avg / total 0.960443 0.960254 0.960004 20807\n", "\n", "Classification report for turbine 11, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 19\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.962494 0.987652 0.974911 18708\n", " 20 0.845963 0.760045 0.800705 1792\n", "\n", "avg / total 0.938257 0.953477 0.945523 20807\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 11, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.989494 0.994955 0.992217 19027\n", " 20 0.951778 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19 0.956231 0.985691 0.970737 18729\n", " 20 0.770586 0.690022 0.728082 2726\n", "\n", "avg / total 0.920121 0.935393 0.927286 21747\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 12, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 6\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.947194 0.971439 0.959163 15861\n", " 20 0.905438 0.866416 0.885498 5592\n", "\n", "avg / total 0.923652 0.931301 0.927254 21747\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 12, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.943473 0.985396 0.963978 16091\n", " 20 0.957451 0.831506 0.890045 5656\n", "\n", "avg / total 0.947108 0.945372 0.944750 21747\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 12, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.985271 0.988231 0.986749 19968\n", " 20 0.866902 0.827431 0.846707 1779\n", "\n", "avg / total 0.975588 0.975077 0.975293 21747\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program 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"stream", "text": [ "Classification report for turbine 12, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.960577 0.960040 0.960308 16091\n", " 20 0.951677 0.887907 0.918687 5656\n", "\n", "avg / total 0.958262 0.941279 0.949483 21747\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 12, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 19 0.988427 0.988031 0.988229 19968\n", " 20 0.888249 0.866779 0.877383 1779\n", "\n", "avg / total 0.980232 0.978112 0.979161 21747\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 12, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 19 0.993144 0.986087 0.989603 20125\n", " 20 0.905347 0.908138 0.906741 1622\n", "\n", "avg / total 0.986596 0.980273 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0.665992 0.758647 2964\n", "\n", "avg / total 0.868814 0.890146 0.876401 21747\n", "\n", "Classification report for turbine 12, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.154321 0.009575 0.018031 2611\n", " 11 0.000000 0.000000 0.000000 703\n", " 12 0.000000 0.000000 0.000000 480\n", " 13 0.000000 0.000000 0.000000 426\n", " 14 0.047619 0.008310 0.014151 361\n", " 15 0.000000 0.000000 0.000000 296\n", " 16 0.000000 0.000000 0.000000 249\n", " 17 0.031056 0.023148 0.026525 216\n", " 18 0.000000 0.000000 0.000000 216\n", " 19 0.812136 0.956509 0.878430 13405\n", " 20 0.439748 0.852011 0.580093 2784\n", "\n", "avg / total 0.576529 0.700189 0.618395 21747\n", "\n", "Classification report for turbine 12, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.001062 0.011765 0.001948 170\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.048387 0.083333 0.061224 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.924630 0.905813 0.915125 15724\n", " 20 0.852285 0.455941 0.594074 5277\n", "\n", "avg / total 0.875525 0.765945 0.806046 21747\n", "\n", "Classification report for turbine 12, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.085890 0.115702 0.098592 121\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.031250 0.027778 0.029412 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.973961 0.970900 0.972428 19725\n", " 20 0.787575 0.730936 0.758199 1613\n", "\n", "avg / total 0.942349 0.935531 0.938847 21747\n", "\n", "Classification report for turbine 12, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.094340 0.041152 0.057307 243\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.029851 0.055556 0.038835 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.033333 0.027778 0.030303 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.980643 0.970215 0.975401 19842\n", " 20 0.743813 0.809316 0.775183 1374\n", "\n", "avg / total 0.942894 0.936957 0.939689 21747\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 12, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.957627 0.265882 0.416206 1275\n", " 11 0.000000 0.000000 0.000000 216\n", " 12 0.018727 0.023148 0.020704 216\n", " 13 0.000000 0.000000 0.000000 216\n", " 14 0.037736 0.010695 0.016667 187\n", " 15 0.000000 0.000000 0.000000 180\n", " 16 0.022222 0.011111 0.014815 180\n", " 17 0.000000 0.000000 0.000000 180\n", " 18 0.000000 0.000000 0.000000 180\n", " 19 0.874899 0.942914 0.907634 17237\n", " 20 0.652580 0.790476 0.714939 1680\n", "\n", "avg / total 0.800710 0.824436 0.799508 21747\n", "\n", "Classification report for turbine 12, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.384688 0.659287 0.485873 1852\n", " 11 0.016393 0.005348 0.008065 374\n", " 12 0.021053 0.005698 0.008969 351\n", " 13 0.000000 0.000000 0.000000 324\n", " 14 0.000000 0.000000 0.000000 324\n", " 15 0.000000 0.000000 0.000000 324\n", " 16 0.000000 0.000000 0.000000 324\n", " 17 0.000000 0.000000 0.000000 303\n", " 18 0.000000 0.000000 0.000000 281\n", " 19 0.864604 0.865748 0.865175 14361\n", " 20 0.514423 0.438375 0.473364 2929\n", "\n", "avg / total 0.673623 0.687083 0.676749 21747\n", "\n", "Classification report for turbine 12, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.003650 0.113402 0.007072 97\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 95\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.911640 0.924666 0.918107 15398\n", " 20 0.933620 0.350296 0.509446 5581\n", "\n", "avg / total 0.885103 0.745114 0.780839 21747\n", "\n", "Classification report for turbine 12, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.466077 0.353468 0.402036 447\n", " 11 0.000000 0.000000 0.000000 151\n", " 12 0.000000 0.000000 0.000000 115\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.017241 0.009259 0.012048 108\n", " 19 0.939677 0.968569 0.953904 19026\n", " 20 0.691099 0.679412 0.685206 1360\n", "\n", "avg / total 0.874989 0.897181 0.885726 21747\n", "\n", "Classification report for turbine 12, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.178218 0.134328 0.153191 134\n", " 11 0.041667 0.012903 0.019704 155\n", " 12 0.019608 0.006944 0.010256 144\n", " 13 0.000000 0.000000 0.000000 144\n", " 14 0.000000 0.000000 0.000000 130\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.947806 0.969945 0.958748 19265\n", " 20 0.742023 0.813850 0.776278 1343\n", "\n", "avg / total 0.886982 0.910470 0.898417 21747\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 12, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.961132 0.984943 0.972892 18729\n", " 20 0.889585 0.752816 0.815506 3018\n", "\n", "avg / total 0.951203 0.952729 0.951050 21747\n", "\n", "Classification report for turbine 12, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.962704 0.975146 0.968885 16094\n", " 20 0.926538 0.892446 0.909173 5653\n", "\n", "avg / total 0.953303 0.953649 0.953363 21747\n", "\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 12, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.943441 0.986887 0.964675 16091\n", " 20 0.957070 0.831683 0.889982 5656\n", "\n", "avg / total 0.946986 0.946521 0.945249 21747\n", "\n", "Classification report for turbine 12, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.990272 0.988982 0.989627 19968\n", " 20 0.878116 0.890950 0.884487 1779\n", "\n", "avg / total 0.981097 0.980963 0.981026 21747\n", "\n", "Classification report for turbine 12, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.993383 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0.023622 144\n", " 12 0.027397 0.027778 0.027586 144\n", " 13 0.046875 0.020833 0.028846 144\n", " 14 0.000000 0.000000 0.000000 144\n", " 15 0.030612 0.020833 0.024793 144\n", " 16 0.000000 0.000000 0.000000 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.916789 0.936602 0.926590 15316\n", " 20 0.851136 0.855186 0.853156 5255\n", "\n", "avg / total 0.852280 0.867062 0.859519 21747\n", "\n", "Classification report for turbine 12, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.011628 0.136364 0.021429 22\n", " 11 0.008621 0.013889 0.010638 144\n", " 12 0.000000 0.000000 0.000000 144\n", " 13 0.000000 0.000000 0.000000 144\n", " 14 0.011236 0.006944 0.008584 144\n", " 15 0.000000 0.000000 0.000000 144\n", " 16 0.000000 0.000000 0.000000 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.859211 0.911915 0.884779 15031\n", " 20 0.924086 0.724829 0.812418 5542\n", "\n", "avg / total 0.829503 0.815285 0.818723 21747\n", "\n", "Classification report for turbine 12, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.166667 0.100000 0.125000 20\n", " 11 0.030303 0.027778 0.028986 108\n", " 12 0.011236 0.009259 0.010152 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.039216 0.037037 0.038095 108\n", " 15 0.022727 0.018519 0.020408 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.948093 0.968236 0.958059 19204\n", " 20 0.835783 0.788427 0.811414 1659\n", "\n", "avg / total 0.901653 0.915713 0.908527 21747\n", "\n", "Classification report for turbine 12, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 1.000000 0.120000 0.214286 25\n", " 11 0.000000 0.000000 0.000000 144\n", " 12 0.000000 0.000000 0.000000 144\n", " 13 0.000000 0.000000 0.000000 144\n", " 14 0.000000 0.000000 0.000000 144\n", " 15 0.000000 0.000000 0.000000 144\n", " 16 0.000000 0.000000 0.000000 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.024390 0.006944 0.010811 144\n", " 19 0.934395 0.972949 0.953282 19001\n", " 20 0.875491 0.851498 0.863328 1569\n", "\n", "avg / total 0.880884 0.911712 0.895516 21747\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 12, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.973763 0.984890 0.979295 18729\n", " 20 0.899073 0.835321 0.866025 3018\n", "\n", "avg / total 0.963398 0.964133 0.963576 21747\n", "\n", "Classification report for turbine 12, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.954512 0.971356 0.962860 16094\n", " 20 0.914137 0.868212 0.890582 5653\n", "\n", "avg / total 0.944017 0.944544 0.944072 21747\n", "\n", "Classification report for turbine 12, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.946146 0.984836 0.965104 16091\n", " 20 0.951180 0.840523 0.892435 5656\n", "\n", "avg / total 0.947455 0.947303 0.946204 21747\n", "\n", "Classification report for turbine 12, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.988962 0.987179 0.988070 19968\n", " 20 0.858953 0.876335 0.867557 1779\n", "\n", "avg / total 0.978327 0.978112 0.978212 21747\n", "\n", "Classification report for turbine 12, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.993875 0.991702 0.992787 20125\n", " 20 0.899760 0.924168 0.911800 1622\n", "\n", "avg / total 0.986855 0.986665 0.986747 21747\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 12, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.961330 0.986225 0.973618 18729\n", " 20 0.898144 0.753810 0.819672 3018\n", "\n", "avg / total 0.952561 0.953971 0.952254 21747\n", "\n", "Classification report for turbine 12, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.966601 0.971045 0.968818 16094\n", " 20 0.916472 0.904475 0.910434 5653\n", "\n", "avg / total 0.953570 0.953741 0.953641 21747\n", "\n", "Classification report for turbine 12, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.958509 0.986328 0.972220 16091\n", " 20 0.957603 0.878536 0.916367 5656\n", "\n", "avg / total 0.958274 0.958293 0.957693 21747\n", "\n", "Classification report for turbine 12, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 15\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.975860 0.990463 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0.731580 0.796421 5171\n", "\n", "avg / total 0.826898 0.858518 0.839577 21812\n", "\n", "Classification report for turbine 13, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.080000 0.007353 0.013468 272\n", " 11 0.007692 0.013889 0.009901 144\n", " 12 0.000000 0.000000 0.000000 144\n", " 13 0.000000 0.000000 0.000000 144\n", " 14 0.000000 0.000000 0.000000 144\n", " 15 0.000000 0.000000 0.000000 134\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.887993 0.953503 0.919582 13162\n", " 20 0.920633 0.879766 0.899735 7344\n", "\n", "avg / total 0.846862 0.871768 0.858073 21812\n", "\n", "Classification report for turbine 13, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.967928 0.973704 0.970807 18938\n", " 20 0.890505 0.766875 0.824079 2874\n", "\n", "avg / total 0.957727 0.946451 0.951474 21812\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 13, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.740741 0.571429 0.645161 35\n", " 11 0.000000 0.000000 0.000000 73\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.955312 0.980954 0.967963 19112\n", " 20 0.867476 0.821360 0.843788 2088\n", "\n", "avg / total 0.921288 0.939070 0.929953 21812\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 13, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.034483 0.062500 0.044444 16\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.942129 0.921105 0.931498 19583\n", " 20 0.718440 0.618815 0.664916 1637\n", "\n", "avg / total 0.899796 0.873464 0.886242 21812\n", "\n", "Classification report for turbine 13, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 35\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.026316 0.013889 0.018182 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.076923 0.013889 0.023529 72\n", " 19 0.927330 0.964859 0.945722 15765\n", " 20 0.928627 0.873620 0.900284 5436\n", "\n", "avg / total 0.902018 0.915184 0.908044 21812\n", "\n", "Classification report for turbine 13, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.961260 0.973812 0.967495 14167\n", " 20 0.965536 0.923479 0.944040 7645\n", "\n", "avg / total 0.962759 0.956171 0.959274 21812\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 13, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.975281 0.981255 0.978259 18938\n", " 20 0.889642 0.821851 0.854404 2874\n", "\n", "avg / total 0.963997 0.960251 0.961939 21812\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 13, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.981999 0.989051 0.985512 19636\n", " 20 0.908818 0.833640 0.869607 2176\n", "\n", "avg / total 0.974699 0.973547 0.973949 21812\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 13, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.973128 0.983467 0.978271 20142\n", " 20 0.771291 0.672455 0.718490 1670\n", "\n", "avg / total 0.957675 0.959655 0.958381 21812\n", "\n", "Classification report for turbine 13, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.973481 0.980742 0.977098 16357\n", " 20 0.940934 0.919890 0.930293 5455\n", "\n", "avg / total 0.965342 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"------------------------------------------------------------------------\n", "Classification report for turbine 13, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 6\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.960656 0.972383 0.966484 19988\n", " 20 0.661228 0.556209 0.604189 1530\n", "\n", "avg / total 0.926704 0.930084 0.928044 21812\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 13, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 10 0.090909 0.000335 0.000668 2984\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.016393 0.027778 0.020619 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.900106 0.977383 0.937154 15608\n", " 20 0.439056 0.780635 0.562015 2644\n", "\n", "avg / total 0.709801 0.794150 0.738885 21812\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 13, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.950859 0.949248 0.950053 14167\n", " 20 0.943604 0.538391 0.685600 7645\n", "\n", "avg / total 0.948316 0.805245 0.857364 21812\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 13, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 10 0.643979 0.093893 0.163891 1310\n", " 11 0.000000 0.000000 0.000000 354\n", " 12 0.000000 0.000000 0.000000 311\n", " 13 0.000000 0.000000 0.000000 252\n", " 14 0.000000 0.000000 0.000000 224\n", " 15 0.000000 0.000000 0.000000 186\n", " 16 0.000000 0.000000 0.000000 180\n", " 17 0.000000 0.000000 0.000000 180\n", " 18 0.000000 0.000000 0.000000 180\n", " 19 0.877713 0.970362 0.921715 17005\n", " 20 0.475522 0.768712 0.587573 1630\n", "\n", "avg / total 0.758492 0.819595 0.772336 21812\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 13, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 10 0.020690 0.040000 0.027273 75\n", " 11 0.000000 0.000000 0.000000 144\n", " 12 0.000000 0.000000 0.000000 144\n", " 13 0.000000 0.000000 0.000000 144\n", " 14 0.000000 0.000000 0.000000 144\n", " 15 0.000000 0.000000 0.000000 144\n", " 16 0.000000 0.000000 0.000000 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.951992 0.972907 0.962336 18935\n", " 20 0.674346 0.780606 0.723596 1650\n", "\n", "avg / total 0.877507 0.903769 0.890235 21812\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 13, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 19 0.972998 0.985751 0.979333 20142\n", " 20 0.795875 0.670060 0.727568 1670\n", "\n", "avg / total 0.959437 0.961581 0.960057 21812\n", "\n", "Classification report for turbine 13, turbine category 7.0\n", " precision 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14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 43\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.899516 0.984125 0.939920 15118\n", " 20 0.882208 0.909998 0.895888 5111\n", "\n", "avg / total 0.830178 0.895333 0.861388 21812\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 13, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.054054 0.561404 0.098613 57\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.898076 0.957682 0.926922 13304\n", " 20 0.952062 0.879531 0.914360 7587\n", "\n", "avg / total 0.879074 0.891528 0.883671 21812\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 13, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.039683 0.035461 0.037453 282\n", " 11 0.000000 0.000000 0.000000 192\n", " 12 0.000000 0.000000 0.000000 180\n", " 13 0.000000 0.000000 0.000000 180\n", " 14 0.000000 0.000000 0.000000 171\n", " 15 0.000000 0.000000 0.000000 144\n", " 16 0.000000 0.000000 0.000000 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.894509 0.966425 0.929077 17513\n", " 20 0.843049 0.760854 0.799845 2718\n", "\n", "avg / total 0.823773 0.871218 0.846115 21812\n", "\n", "Classification report for turbine 13, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.029070 0.031250 0.030120 160\n", " 11 0.000000 0.000000 0.000000 180\n", " 12 0.000000 0.000000 0.000000 180\n", " 13 0.000000 0.000000 0.000000 180\n", " 14 0.090909 0.005556 0.010471 180\n", " 15 0.000000 0.000000 0.000000 180\n", " 16 0.000000 0.000000 0.000000 180\n", " 17 0.000000 0.000000 0.000000 180\n", " 18 0.000000 0.000000 0.000000 180\n", " 19 0.912937 0.976660 0.943724 18295\n", " 20 0.845128 0.859677 0.852340 1917\n", "\n", "avg / total 0.840973 0.895012 0.866774 21812\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 13, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 19 0.971307 0.984858 0.978035 20142\n", " 20 0.780418 0.649102 0.708728 1670\n", "\n", "avg / total 0.956692 0.959151 0.957416 21812\n", "\n", "Classification report for turbine 13, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 19 0.970585 0.982393 0.976453 16357\n", " 20 0.945205 0.910724 0.927644 5455\n", "\n", "avg / total 0.964238 0.964469 0.964246 21812\n", "\n", "Classification report for turbine 13, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 4\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.971591 0.978593 0.975079 14154\n", " 20 0.922975 0.946783 0.934727 7366\n", "\n", "avg / total 0.942166 0.954750 0.948399 21812\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 13, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 14 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 19 0.979391 0.978667 0.979029 18938\n", " 20 0.859722 0.861517 0.860619 2874\n", "\n", "avg / total 0.963623 0.963231 0.963427 21812\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 13, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 19 0.986259 0.990579 0.988414 19636\n", " 20 0.911483 0.875460 0.893108 2176\n", "\n", "avg / total 0.978799 0.979094 0.978906 21812\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 13, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 119\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.925754 0.983130 0.953580 19265\n", " 20 0.742813 0.611253 0.670642 1564\n", "\n", "avg / total 0.870916 0.912158 0.890317 21812\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 13, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.015707 0.025210 0.019355 119\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.066667 0.013889 0.022989 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.938261 0.954795 0.946456 16060\n", " 20 0.856591 0.832707 0.844480 5057\n", "\n", "avg / total 0.889736 0.896250 0.892837 21812\n", "\n", "Classification report for turbine 13, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 16\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.018182 0.013889 0.015748 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.917382 0.951456 0.934108 13596\n", " 20 0.957282 0.861228 0.906718 7624\n", "\n", "avg / total 0.906490 0.894141 0.899234 21812\n", "\n", "Classification report for turbine 13, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.748538 0.186047 0.298021 688\n", " 11 0.000000 0.000000 0.000000 477\n", " 12 0.000000 0.000000 0.000000 396\n", " 13 0.000000 0.000000 0.000000 396\n", " 14 0.000000 0.000000 0.000000 375\n", " 15 0.000000 0.000000 0.000000 360\n", " 16 0.000000 0.000000 0.000000 360\n", " 17 0.000000 0.000000 0.000000 360\n", " 18 0.000000 0.000000 0.000000 338\n", " 19 0.824827 0.974931 0.893619 15996\n", " 20 0.617908 0.774927 0.687567 2066\n", "\n", "avg / total 0.687031 0.794242 0.729868 21812\n", "\n", "Classification report for turbine 13, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.003367 0.062500 0.006390 16\n", " 11 0.018519 0.009259 0.012346 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.034483 0.009259 0.014599 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.944090 0.963734 0.953811 18888\n", " 20 0.840501 0.755382 0.795671 2044\n", "\n", "avg / total 0.896559 0.905465 0.900648 21812\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 13, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.579470 0.596252 0.587741 587\n", " 11 0.000000 0.000000 0.000000 112\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.071429 0.018519 0.029412 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.024390 0.009259 0.013423 108\n", " 19 0.933327 0.956135 0.944593 19355\n", " 20 0.506388 0.435130 0.468062 1002\n", "\n", "avg / total 0.867524 0.884605 0.875721 21812\n", "\n", "Classification report for turbine 13, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.311000 0.438605 0.363941 1979\n", " 11 0.009804 0.018519 0.012821 108\n", " 12 0.069930 0.092593 0.079681 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.902012 0.916725 0.909309 15695\n", " 20 0.546367 0.415699 0.472160 3274\n", "\n", "avg / total 0.759672 0.762379 0.758651 21812\n", "\n", "Classification report for turbine 13, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.108434 0.384798 0.169191 421\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.002326 0.013889 0.003984 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.919710 0.940287 0.929885 13498\n", " 20 0.953819 0.733907 0.829536 7317\n", "\n", "avg / total 0.891214 0.835549 0.856997 21812\n", "\n", "Classification report for turbine 13, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.244510 0.533546 0.335341 313\n", " 11 0.000000 0.000000 0.000000 224\n", " 12 0.035294 0.027027 0.030612 222\n", " 13 0.100000 0.008439 0.015564 237\n", " 14 0.000000 0.000000 0.000000 183\n", " 15 0.000000 0.000000 0.000000 180\n", " 16 0.000000 0.000000 0.000000 180\n", " 17 0.000000 0.000000 0.000000 180\n", " 18 0.000000 0.000000 0.000000 180\n", " 19 0.896185 0.959559 0.926790 17408\n", " 20 0.800374 0.683433 0.737295 2505\n", "\n", "avg / total 0.812113 0.852329 0.829632 21812\n", "\n", "Classification report for turbine 13, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.562500 0.036496 0.068545 1233\n", " 11 0.000000 0.000000 0.000000 365\n", " 12 0.205882 0.114007 0.146751 307\n", " 13 0.000000 0.000000 0.000000 252\n", " 14 0.000000 0.000000 0.000000 252\n", " 15 0.000000 0.000000 0.000000 252\n", " 16 0.000000 0.000000 0.000000 252\n", " 17 0.000000 0.000000 0.000000 252\n", " 18 0.000000 0.000000 0.000000 252\n", " 19 0.895188 0.971017 0.931562 17838\n", " 20 0.180527 0.639138 0.281534 557\n", "\n", "avg / total 0.771396 0.814093 0.774967 21812\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 13, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.971419 0.985453 0.978386 20142\n", " 20 0.787527 0.650299 0.712365 1670\n", "\n", "avg / total 0.957339 0.959793 0.958018 21812\n", "\n", "Classification report for turbine 13, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.969494 0.983126 0.976263 16357\n", " 20 0.947177 0.907241 0.926779 5455\n", "\n", "avg / total 0.963913 0.964148 0.963887 21812\n", "\n", "Classification report for turbine 13, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.974388 0.977483 0.975933 14167\n", " 20 0.958026 0.952387 0.955198 7645\n", "\n", "avg / total 0.968653 0.968687 0.968666 21812\n", "\n", "Classification report for turbine 13, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 4\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.961615 0.984316 0.972833 18681\n", " 20 0.877695 0.831631 0.854042 2839\n", "\n", "avg / total 0.937819 0.951265 0.944348 21812\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 13, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 19 0.983082 0.982481 0.982781 19636\n", " 20 0.905206 0.846967 0.875119 2176\n", "\n", "avg / total 0.975313 0.968962 0.972041 21812\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 13, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 56\n", " 11 0.000000 0.000000 0.000000 324\n", " 12 0.000000 0.000000 0.000000 324\n", " 13 0.000000 0.000000 0.000000 324\n", " 14 0.000000 0.000000 0.000000 324\n", " 15 0.000000 0.000000 0.000000 315\n", " 16 0.000000 0.000000 0.000000 288\n", " 17 0.000000 0.000000 0.000000 288\n", " 18 0.000000 0.000000 0.000000 288\n", " 19 0.860012 0.985187 0.918353 17822\n", " 20 0.704155 0.673749 0.688616 1459\n", "\n", "avg / total 0.749793 0.850037 0.796423 21812\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 13, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.384615 0.416667 0.400000 12\n", " 11 0.034483 0.055556 0.042553 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.928030 0.906824 0.917304 15798\n", " 20 0.934337 0.881128 0.906952 5426\n", "\n", "avg / total 0.904907 0.876398 0.890361 21812\n", "\n", "Classification report for turbine 13, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.011173 0.090909 0.019900 22\n", " 11 0.014085 0.006944 0.009302 144\n", " 12 0.000000 0.000000 0.000000 144\n", " 13 0.000000 0.000000 0.000000 144\n", " 14 0.000000 0.000000 0.000000 144\n", " 15 0.000000 0.000000 0.000000 144\n", " 16 0.000000 0.000000 0.000000 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.893747 0.940138 0.916356 13197\n", " 20 0.934551 0.907674 0.920916 7441\n", "\n", "avg / total 0.859667 0.878599 0.868672 21812\n", "\n", "Classification report for turbine 13, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.142857 0.052632 0.076923 19\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.025000 0.009259 0.013514 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.944019 0.960118 0.952000 18354\n", " 20 0.791033 0.808544 0.799693 2575\n", "\n", "avg / total 0.887990 0.903448 0.895614 21812\n", "\n", "Classification report for turbine 13, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.250000 0.117647 0.160000 17\n", " 11 0.076923 0.018519 0.029851 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.023810 0.009259 0.013333 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.014085 0.009259 0.011173 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.946818 0.973641 0.960042 18779\n", " 20 0.910671 0.876394 0.893204 2152\n", "\n", "avg / total 0.905772 0.924995 0.915065 21812\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 13, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.973074 0.983219 0.978120 20142\n", " 20 0.768493 0.671856 0.716933 1670\n", "\n", "avg / total 0.957411 0.959380 0.958123 21812\n", "\n", "Classification report for turbine 13, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.972790 0.981354 0.977053 16357\n", " 20 0.942572 0.917690 0.929965 5455\n", "\n", "avg / total 0.965232 0.965432 0.965276 21812\n", "\n", "Classification report for turbine 13, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.974224 0.976424 0.975323 14167\n", " 20 0.956128 0.952126 0.954122 7645\n", "\n", "avg / total 0.967881 0.967908 0.967892 21812\n", "\n", "Classification report for turbine 13, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.972848 0.985690 0.979227 18938\n", " 20 0.896723 0.818720 0.855948 2874\n", "\n", "avg / total 0.962817 0.963690 0.962983 21812\n", "\n", "Classification report for turbine 13, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.991176 0.989662 0.990418 19636\n", " 20 0.907978 0.920496 0.914194 2176\n", "\n", "avg / total 0.982876 0.982762 0.982814 21812\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 13, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.974467 0.985304 0.979856 20142\n", " 20 0.795297 0.688623 0.738126 1670\n", "\n", "avg / total 0.960749 0.962589 0.961348 21812\n", "\n", "Classification report for turbine 13, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.973734 0.981354 0.977529 16357\n", " 20 0.942745 0.920623 0.931553 5455\n", "\n", "avg / total 0.965984 0.966165 0.966031 21812\n", "\n", "Classification report for turbine 13, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.973020 0.980095 0.976545 14167\n", " 20 0.962609 0.949640 0.956081 7645\n", "\n", "avg / total 0.969371 0.969421 0.969372 21812\n", "\n", "Classification report for turbine 13, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 13\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.959808 0.984685 0.972087 18674\n", " 20 0.879050 0.822348 0.849754 2837\n", "\n", "avg / total 0.936059 0.949982 0.942761 21812\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 13, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 14 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.984281 0.982176 0.983227 19636\n", " 20 0.906356 0.858456 0.881756 2176\n", "\n", "avg / total 0.976507 0.969833 0.973104 21812\n", "\n", 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0.978170 0.952108 0.964768 21778\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 14, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.777778 0.148936 0.250000 94\n", " 11 0.196429 0.041985 0.069182 262\n", " 12 0.092593 0.025126 0.039526 199\n", " 13 0.000000 0.000000 0.000000 180\n", " 14 0.000000 0.000000 0.000000 146\n", " 15 0.000000 0.000000 0.000000 144\n", " 16 0.000000 0.000000 0.000000 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.933565 0.985303 0.958737 19596\n", " 20 0.689777 0.809655 0.744924 725\n", "\n", "avg / total 0.869558 0.914914 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0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.991854 0.992615 0.992235 20854\n", " 20 0.857961 0.810606 0.833612 924\n", "\n", "avg / total 0.986173 0.984893 0.985505 21778\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 14, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.991396 0.995058 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warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 14, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 19 0.990969 0.994533 0.992748 20854\n", " 20 0.874251 0.790043 0.830017 924\n", "\n", "avg / total 0.986017 0.985857 0.985844 21778\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 14, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 19 0.991864 0.994291 0.993076 20843\n", " 20 0.917775 0.811765 0.861521 935\n", "\n", "avg / total 0.988683 0.986454 0.987428 21778\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 14, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.989225 0.993678 0.991446 20880\n", " 20 0.835821 0.748330 0.789659 898\n", "\n", "avg / total 0.982899 0.983561 0.983126 21778\n", "\n", "Classification report for turbine 14, turbine category 4.0\n", " precision 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"------------------------------------------------------------------------\n", "Classification report for turbine 14, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 13\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.972660 0.957287 0.964912 20626\n", " 20 0.771307 0.638073 0.698392 851\n", "\n", "avg / total 0.951349 0.931582 0.941161 21778\n", "\n", "Classification report for turbine 14, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.993187 0.976742 0.984896 20896\n", " 20 0.834129 0.792517 0.812791 882\n", "\n", "avg / total 0.986746 0.969281 0.977926 21778\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 14, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.018018 0.142857 0.032000 14\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.899199 0.896242 0.897718 17030\n", " 20 0.949147 0.682299 0.793900 4158\n", "\n", "avg / total 0.884386 0.831206 0.853596 21778\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 14, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 200\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.948985 0.988729 0.968449 19962\n", " 20 0.682298 0.773936 0.725234 752\n", "\n", "avg / total 0.893412 0.933006 0.912736 21778\n", "\n", "Classification report for turbine 14, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.991521 0.987478 0.989495 20843\n", " 20 0.903431 0.760428 0.825784 935\n", "\n", "avg / total 0.987739 0.977730 0.982467 21778\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 14, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 19 0.988044 0.993439 0.990734 20880\n", " 20 0.825255 0.720490 0.769322 898\n", "\n", "avg / total 0.981332 0.982184 0.981604 21778\n", "\n", "Classification report for turbine 14, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 19 0.994067 0.994257 0.994162 20896\n", " 20 0.863326 0.859410 0.861364 882\n", "\n", "avg / total 0.988772 0.988796 0.988784 21778\n", "\n", "Classification report for turbine 14, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 19 0.928396 0.989150 0.957811 17604\n", " 20 0.936797 0.678246 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"------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 14, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 19 0.987667 0.993391 0.990521 20880\n", " 20 0.822394 0.711581 0.762985 898\n", "\n", "avg / total 0.980852 0.981771 0.981138 21778\n", "\n", "Classification report for turbine 14, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 19 0.993783 0.994449 0.994116 20896\n", " 20 0.866359 0.852608 0.859429 882\n", "\n", "avg / total 0.988622 0.988704 0.988661 21778\n", "\n", "Classification report for turbine 14, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 19 0.918020 0.989150 0.952259 17604\n", " 20 0.932028 0.627456 0.750000 4174\n", "\n", "avg / total 0.920705 0.919827 0.913493 21778\n", "\n", "Classification report for turbine 14, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 19 0.993056 0.994390 0.993722 20854\n", " 20 0.869420 0.843074 0.856044 924\n", "\n", "avg / total 0.987811 0.987970 0.987881 21778\n", "\n", "Classification report for turbine 14, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 19 0.992162 0.996066 0.994110 20843\n", " 20 0.903869 0.824599 0.862416 935\n", "\n", "avg / total 0.988372 0.988704 0.988456 21778\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 14, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.987994 0.961638 0.974638 20880\n", " 20 0.800000 0.659243 0.722833 898\n", "\n", "avg / total 0.980242 0.949169 0.964255 21778\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 14, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.993189 0.983968 0.988557 20896\n", " 20 0.845588 0.782313 0.812721 882\n", "\n", "avg / total 0.987211 0.975801 0.981436 21778\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 14, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.012048 0.004600 0.006658 1087\n", " 11 0.000000 0.000000 0.000000 144\n", " 12 0.000000 0.000000 0.000000 144\n", " 13 0.000000 0.000000 0.000000 118\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.873517 0.986247 0.926465 16869\n", " 20 0.839238 0.620092 0.713210 3056\n", "\n", "avg / total 0.794984 0.851180 0.818043 21778\n", "\n", "Classification report for turbine 14, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 21\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.111111 0.009346 0.017241 107\n", " 14 0.000000 0.000000 0.000000 98\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.956453 0.987838 0.971892 20144\n", " 20 0.811024 0.683628 0.741897 904\n", "\n", "avg / total 0.918902 0.942143 0.929852 21778\n", "\n", "Classification report for 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and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 14, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.991540 0.994773 0.993154 20854\n", " 20 0.882494 0.796537 0.837315 924\n", "\n", "avg / total 0.986913 0.986362 0.986542 21778\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 14, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 6\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.978831 0.994114 0.986414 20559\n", " 20 0.902844 0.823784 0.861504 925\n", "\n", "avg / total 0.962390 0.973459 0.967792 21778\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 14, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.214286 0.036585 0.062500 164\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.958961 0.969322 0.964113 20177\n", " 20 0.813218 0.657375 0.727039 861\n", "\n", "avg / total 0.922228 0.924327 0.922451 21778\n", "\n", "Classification report for turbine 14, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.992360 0.988371 0.990362 20896\n", " 20 0.858333 0.817460 0.837398 882\n", "\n", "avg / total 0.986932 0.981449 0.984167 21778\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 14, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.043257 0.809524 0.082126 21\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.894879 0.899017 0.896943 17300\n", " 20 0.934317 0.607340 0.736154 4169\n", "\n", "avg / total 0.889773 0.831206 0.853516 21778\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 14, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 8\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.967016 0.990947 0.978835 20325\n", " 20 0.807955 0.818182 0.813036 869\n", "\n", "avg / total 0.934737 0.957480 0.945971 21778\n", "\n", "Classification report for turbine 14, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.071429 0.025000 0.037037 160\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.964419 0.992303 0.978163 20268\n", " 20 0.724566 0.754522 0.739241 774\n", "\n", "avg / total 0.923826 0.950501 0.936886 21778\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 14, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.986893 0.977251 0.982048 20880\n", " 20 0.832664 0.692650 0.756231 898\n", "\n", "avg / total 0.980533 0.965516 0.972737 21778\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 14, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.993091 0.990572 0.991830 20896\n", " 20 0.846330 0.836735 0.841505 882\n", "\n", "avg / total 0.987147 0.984342 0.985742 21778\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 14, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 278\n", " 11 0.000000 0.000000 0.000000 184\n", " 12 0.000000 0.000000 0.000000 144\n", " 13 0.000000 0.000000 0.000000 144\n", " 14 0.000000 0.000000 0.000000 118\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.860667 0.987778 0.919852 16528\n", " 20 0.908277 0.641772 0.752114 3950\n", "\n", "avg / total 0.817927 0.866057 0.834520 21778\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 14, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.063830 0.088235 0.074074 34\n", " 11 0.016949 0.013699 0.015152 73\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.034483 0.013889 0.019802 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.965040 0.982160 0.973525 20292\n", " 20 0.821002 0.786286 0.803269 875\n", "\n", "avg / total 0.932448 0.946965 0.939603 21778\n", "\n", "Classification report for turbine 14, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 170\n", " 11 0.000000 0.000000 0.000000 78\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.963505 0.990277 0.976708 20262\n", " 20 0.679505 0.646597 0.662643 764\n", "\n", "avg / total 0.920272 0.944026 0.931964 21778\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 14, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 61\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.977809 0.993551 0.985617 20622\n", " 20 0.793689 0.810409 0.801962 807\n", "\n", "avg / total 0.955316 0.970842 0.963016 21778\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 14, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 145\n", " 11 0.000000 0.000000 0.000000 154\n", " 12 0.000000 0.000000 0.000000 144\n", " 13 0.000000 0.000000 0.000000 128\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.416667 0.046296 0.083333 108\n", " 19 0.947043 0.990816 0.968435 19926\n", " 20 0.702227 0.808367 0.751568 741\n", "\n", "avg / total 0.892466 0.934291 0.912065 21778\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 14, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 90\n", " 11 0.000000 0.000000 0.000000 74\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.940145 0.988744 0.963832 17236\n", " 20 0.872785 0.775684 0.821375 3874\n", "\n", "avg / total 0.899325 0.920516 0.908927 21778\n", "\n", "Classification report for turbine 14, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 11\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.976591 0.992073 0.984271 20563\n", " 20 0.856280 0.774017 0.813073 916\n", "\n", "avg / total 0.958122 0.969281 0.963557 21778\n", "\n", "Classification report for turbine 14, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.990855 0.992851 0.991852 20843\n", " 20 0.927500 0.793583 0.855331 935\n", "\n", "avg / total 0.988135 0.984296 0.985991 21778\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 14, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 56\n", " 11 0.045455 0.003086 0.005780 324\n", " 12 0.000000 0.000000 0.000000 324\n", " 13 0.000000 0.000000 0.000000 324\n", " 14 0.045455 0.003086 0.005780 324\n", " 15 0.000000 0.000000 0.000000 324\n", " 16 0.000000 0.000000 0.000000 324\n", " 17 0.000000 0.000000 0.000000 324\n", " 18 0.000000 0.000000 0.000000 324\n", " 19 0.866320 0.988456 0.923366 18364\n", " 20 0.718706 0.667102 0.691943 766\n", "\n", "avg / total 0.757144 0.857058 0.803126 21778\n", "\n", "Classification report for 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0.000000 144\n", " 18 0.083333 0.006944 0.012821 144\n", " 19 0.875755 0.948184 0.910532 16964\n", " 20 0.891845 0.570722 0.696031 3641\n", "\n", "avg / total 0.833330 0.835430 0.827149 21778\n", "\n", "Classification report for turbine 14, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.062500 0.076923 0.068966 13\n", " 11 0.045455 0.013889 0.021277 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.962789 0.979784 0.971212 20281\n", " 20 0.860406 0.746696 0.799528 908\n", "\n", "avg / total 0.932669 0.943659 0.937898 21778\n", "\n", "Classification report for turbine 14, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.333333 0.076923 0.125000 13\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.962607 0.978091 0.970287 20266\n", " 20 0.901373 0.782232 0.837587 923\n", "\n", "avg / total 0.934176 0.943383 0.938496 21778\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 14, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.988084 0.992816 0.990444 20880\n", " 20 0.812030 0.721604 0.764151 898\n", "\n", "avg / total 0.980824 0.981633 0.981113 21778\n", "\n", "Classification report for turbine 14, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.993543 0.994066 0.993804 20896\n", " 20 0.857635 0.846939 0.852253 882\n", "\n", "avg / total 0.988039 0.988107 0.988072 21778\n", 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"Classification report for turbine 14, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 19 0.992629 0.994438 0.993532 20854\n", " 20 0.874572 0.830087 0.851749 924\n", "\n", "avg / total 0.987620 0.987464 0.987517 21778\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 14, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.992121 0.996785 0.994448 20843\n", " 20 0.919952 0.823529 0.869074 935\n", "\n", "avg / total 0.989022 0.989347 0.989065 21778\n", "\n", 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0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.979499 0.994650 0.987016 20559\n", " 20 0.863485 0.852136 0.857773 913\n", "\n", "avg / total 0.960872 0.974699 0.967729 21778\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 14, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.991550 0.996498 0.994018 20843\n", " 20 0.917676 0.810695 0.860875 935\n", "\n", "avg / total 0.988378 0.988521 0.988301 21778\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 15, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 19 0.961959 0.948552 0.955208 15569\n", " 20 0.867576 0.816087 0.841044 4600\n", "\n", "avg / total 0.940433 0.918340 0.929171 20169\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 15, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.021277 0.062500 0.031746 48\n", " 11 0.000000 0.000000 0.000000 85\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 41\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.940952 0.976210 0.958257 13157\n", " 20 0.943715 0.926576 0.935067 6442\n", "\n", "avg / total 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20169\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 15, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 242\n", " 11 0.020000 0.002778 0.004878 360\n", " 12 0.114286 0.011111 0.020253 360\n", " 13 0.000000 0.000000 0.000000 360\n", " 14 0.090909 0.002778 0.005391 360\n", " 15 0.114286 0.011111 0.020253 360\n", " 16 0.000000 0.000000 0.000000 360\n", " 17 0.000000 0.000000 0.000000 360\n", " 18 0.000000 0.000000 0.000000 360\n", " 19 0.787695 0.960075 0.865385 12749\n", " 20 0.833034 0.863658 0.848069 4298\n", "\n", "avg / total 0.681488 0.791413 0.728646 20169\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 15, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.006135 0.031746 0.010283 63\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.952704 0.945926 0.949303 13352\n", " 20 0.948520 0.891896 0.919337 6466\n", "\n", "avg / total 0.934802 0.912242 0.923207 20169\n", "\n", "Classification report for turbine 15, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.938227 0.948559 0.943365 13258\n", " 20 0.958808 0.865577 0.909810 6911\n", "\n", "avg / total 0.945279 0.920125 0.931867 20169\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 15, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.500000 0.059524 0.106383 84\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.952700 0.967413 0.960000 14699\n", " 20 0.911151 0.899176 0.905124 5098\n", "\n", "avg / total 0.926709 0.932570 0.928866 20169\n", "\n", "Classification report for turbine 15, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.057471 0.034247 0.042918 146\n", " 11 0.000000 0.000000 0.000000 118\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.040000 0.009259 0.015038 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.936192 0.976019 0.955691 15679\n", " 20 0.902005 0.920461 0.911140 3470\n", "\n", "avg / total 0.883595 0.917398 0.900085 20169\n", "\n", "------------------------------------------------------------------------\n", "Classification report for 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"Classification report for turbine 15, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.990730 0.988394 0.989560 16543\n", " 20 0.947613 0.957805 0.952681 3626\n", "\n", "avg / total 0.982978 0.982895 0.982930 20169\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 15, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 19 0.957996 0.963903 0.960940 15569\n", " 20 0.875222 0.856957 0.865993 4600\n", "\n", "avg / total 0.939117 0.939511 0.939285 20169\n", "\n", "Classification report for turbine 15, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 327\n", " 11 0.000000 0.000000 0.000000 221\n", " 12 0.000000 0.000000 0.000000 180\n", " 13 0.000000 0.000000 0.000000 145\n", " 14 0.000000 0.000000 0.000000 144\n", " 15 0.000000 0.000000 0.000000 127\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 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0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.922464 0.944316 0.933262 13002\n", " 20 0.958636 0.883714 0.919652 6871\n", "\n", "avg / total 0.921249 0.909812 0.914929 20169\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 15, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.023810 0.066667 0.035088 15\n", " 11 0.000000 0.000000 0.000000 37\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.951221 0.973905 0.962429 14677\n", " 20 0.932717 0.895143 0.913544 5188\n", "\n", "avg / total 0.932142 0.939015 0.935374 20169\n", "\n", "Classification report for turbine 15, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 12\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.971581 0.972716 0.972148 16273\n", " 20 0.929558 0.935762 0.932650 3596\n", "\n", "avg / total 0.949637 0.951658 0.950646 20169\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 15, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.960407 0.928576 0.944223 15569\n", " 20 0.868828 0.768913 0.815823 4600\n", "\n", "avg / total 0.939520 0.892161 0.914939 20169\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 15, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 10 0.168224 0.017459 0.031634 1031\n", " 11 0.000000 0.000000 0.000000 624\n", " 12 0.000000 0.000000 0.000000 504\n", " 13 0.065217 0.005952 0.010909 504\n", " 14 0.000000 0.000000 0.000000 474\n", " 15 0.000000 0.000000 0.000000 373\n", " 16 0.000000 0.000000 0.000000 335\n", " 17 0.000000 0.000000 0.000000 288\n", " 18 0.000000 0.000000 0.000000 267\n", " 19 0.788974 0.940868 0.858252 11043\n", " 20 0.658202 0.943292 0.775372 4726\n", "\n", "avg / total 0.596441 0.737220 0.653488 20169\n", "\n", "Classification report for turbine 15, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 10 0.071563 0.044864 0.055152 847\n", " 11 0.013889 0.006568 0.008919 609\n", " 12 0.000000 0.000000 0.000000 352\n", " 13 0.000000 0.000000 0.000000 252\n", " 14 0.000000 0.000000 0.000000 234\n", " 15 0.000000 0.000000 0.000000 144\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.150000 0.041667 0.065217 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.820612 0.941882 0.877075 11666\n", " 20 0.796610 0.739272 0.766871 5849\n", "\n", "avg / total 0.709629 0.761416 0.732522 20169\n", "\n", "Classification report for turbine 15, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 10 0.110211 0.090909 0.099634 748\n", " 11 0.007937 0.004115 0.005420 243\n", " 12 0.000000 0.000000 0.000000 203\n", " 13 0.000000 0.000000 0.000000 154\n", " 14 0.000000 0.000000 0.000000 144\n", " 15 0.000000 0.000000 0.000000 144\n", " 16 0.000000 0.000000 0.000000 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.893134 0.951873 0.921569 13776\n", " 20 0.761850 0.765549 0.763695 4325\n", "\n", "avg / total 0.777589 0.817740 0.796983 20169\n", "\n", "Classification report for turbine 15, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 10 0.099432 0.047945 0.064695 730\n", " 11 0.000000 0.000000 0.000000 432\n", " 12 0.064815 0.016204 0.025926 432\n", " 13 0.051724 0.006944 0.012245 432\n", " 14 0.031250 0.004808 0.008333 416\n", " 15 0.008621 0.002558 0.003945 391\n", " 16 0.000000 0.000000 0.000000 360\n", " 17 0.000000 0.000000 0.000000 360\n", " 18 0.000000 0.000000 0.000000 360\n", " 19 0.826785 0.958357 0.887723 13856\n", " 20 0.630653 0.836667 0.719198 2400\n", "\n", "avg / total 0.649948 0.760325 0.698849 20169\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 15, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 19 0.960643 0.964160 0.962398 15569\n", " 20 0.877174 0.866304 0.871705 4600\n", "\n", "avg / total 0.941606 0.941841 0.941713 20169\n", "\n", "Classification report for turbine 15, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 29\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 38\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.956276 0.976512 0.966288 13326\n", " 20 0.923945 0.961002 0.942109 6308\n", "\n", "avg / total 0.920798 0.945758 0.933094 20169\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 15, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 96\n", " 11 0.000000 0.000000 0.000000 144\n", " 12 0.500000 0.049296 0.089744 142\n", " 13 0.000000 0.000000 0.000000 92\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.906237 0.983087 0.943099 12830\n", " 20 0.942181 0.858040 0.898145 6685\n", "\n", "avg / total 0.892285 0.910110 0.898249 20169\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 15, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 1045\n", " 11 0.000000 0.000000 0.000000 411\n", " 12 0.000000 0.000000 0.000000 234\n", " 13 0.000000 0.000000 0.000000 184\n", " 14 0.000000 0.000000 0.000000 144\n", " 15 0.000000 0.000000 0.000000 144\n", " 16 0.000000 0.000000 0.000000 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.000000 0.000000 0.000000 123\n", " 19 0.878208 0.981710 0.927079 13559\n", " 20 0.716192 0.877632 0.788736 4037\n", "\n", "avg / total 0.733744 0.835639 0.781119 20169\n", "\n", "Classification report for turbine 15, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 396\n", " 11 0.000000 0.000000 0.000000 165\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 95\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.940133 0.975508 0.957494 15760\n", " 20 0.828375 0.891351 0.858710 3249\n", "\n", "avg / total 0.868060 0.905846 0.886512 20169\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 15, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 107\n", " 11 0.000000 0.000000 0.000000 180\n", " 12 0.000000 0.000000 0.000000 180\n", " 13 0.000000 0.000000 0.000000 180\n", " 14 0.000000 0.000000 0.000000 176\n", " 15 0.000000 0.000000 0.000000 144\n", " 16 0.000000 0.000000 0.000000 161\n", " 17 0.000000 0.000000 0.000000 180\n", " 18 0.000000 0.000000 0.000000 180\n", " 19 0.904066 0.964048 0.933094 14575\n", " 20 0.778307 0.875548 0.824069 4106\n", "\n", "avg / total 0.811765 0.874907 0.842058 20169\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 15, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 2063\n", " 11 0.000000 0.000000 0.000000 150\n", " 12 0.000000 0.000000 0.000000 144\n", " 13 0.000000 0.000000 0.000000 144\n", " 14 0.000000 0.000000 0.000000 144\n", " 15 0.000000 0.000000 0.000000 144\n", " 16 0.045455 0.006944 0.012048 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.917549 0.965348 0.940842 12842\n", " 20 0.583173 0.886264 0.703460 4106\n", "\n", "avg / total 0.703268 0.795131 0.742349 20169\n", "\n", "Classification report for turbine 15, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.021021 0.082353 0.033493 85\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.103093 0.185185 0.132450 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.881171 0.928634 0.904280 12513\n", " 20 0.930790 0.822126 0.873090 6707\n", "\n", "avg / total 0.856851 0.850860 0.852210 20169\n", "\n", "Classification report for turbine 15, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.003195 0.007519 0.004484 133\n", " 11 0.000000 0.000000 0.000000 216\n", " 12 0.043478 0.004630 0.008368 216\n", " 13 0.011364 0.004630 0.006579 216\n", " 14 0.083333 0.004630 0.008772 216\n", " 15 0.000000 0.000000 0.000000 216\n", " 16 0.066667 0.004630 0.008658 216\n", " 17 0.000000 0.000000 0.000000 213\n", " 18 0.000000 0.000000 0.000000 180\n", " 19 0.874183 0.968674 0.919006 13535\n", " 20 0.860781 0.828761 0.844468 4812\n", "\n", "avg / total 0.794230 0.848034 0.818579 20169\n", "\n", "Classification report for turbine 15, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.105528 0.076923 0.088983 273\n", " 11 0.000000 0.000000 0.000000 432\n", " 12 0.052632 0.002315 0.004435 432\n", " 13 0.005525 0.002315 0.003263 432\n", " 14 0.000000 0.000000 0.000000 416\n", " 15 0.000000 0.000000 0.000000 396\n", " 16 0.100000 0.002525 0.004926 396\n", " 17 0.000000 0.000000 0.000000 396\n", " 18 0.000000 0.000000 0.000000 394\n", " 19 0.829139 0.965160 0.891993 13892\n", " 20 0.685319 0.876753 0.769305 2710\n", "\n", "avg / total 0.667814 0.783777 0.719221 20169\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 15, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 19 0.958394 0.967628 0.962989 15569\n", " 20 0.886742 0.857826 0.872044 4600\n", "\n", "avg / total 0.942052 0.942585 0.942247 20169\n", "\n", "Classification report for turbine 15, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 19 0.977520 0.979952 0.978734 13667\n", " 20 0.957638 0.952630 0.955127 6502\n", "\n", "avg / total 0.971110 0.971144 0.971124 20169\n", "\n", "Classification report for turbine 15, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 33\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.933401 0.984434 0.958238 13041\n", " 20 0.951208 0.896430 0.923007 6807\n", "\n", "avg / total 0.924555 0.939065 0.931097 20169\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 15, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.966462 0.979157 0.972768 14921\n", " 20 0.945509 0.902630 0.923572 5248\n", "\n", "avg / total 0.961010 0.959244 0.959967 20169\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 15, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.990219 0.985311 0.987759 16543\n", " 20 0.937737 0.955323 0.946448 3626\n", "\n", "avg / total 0.980784 0.979920 0.980332 20169\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 15, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.733690 0.384529 0.504597 1784\n", " 11 0.166922 0.071995 0.100600 1514\n", " 12 0.106918 0.013209 0.023513 1287\n", " 13 0.052083 0.004762 0.008726 1050\n", " 14 0.000000 0.000000 0.000000 795\n", " 15 0.000000 0.000000 0.000000 533\n", " 16 0.011905 0.002012 0.003442 497\n", " 17 0.000000 0.000000 0.000000 448\n", " 18 0.022727 0.004988 0.008180 401\n", " 19 0.573548 0.918656 0.706194 9134\n", " 20 0.549505 0.651504 0.596173 2726\n", "\n", "avg / total 0.421720 0.544747 0.454781 20169\n", "\n", "Classification report for turbine 15, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.115865 0.570896 0.192635 536\n", " 11 0.088512 0.144615 0.109813 650\n", " 12 0.045330 0.057996 0.050887 569\n", " 13 0.032641 0.023109 0.027060 476\n", " 14 0.013624 0.010870 0.012092 460\n", " 15 0.011869 0.011527 0.011696 347\n", " 16 0.015810 0.012346 0.013865 324\n", " 17 0.005376 0.003086 0.003922 324\n", " 18 0.009524 0.003086 0.004662 324\n", " 19 0.757484 0.743420 0.750386 10449\n", " 20 0.860441 0.587391 0.698168 5710\n", "\n", "avg / total 0.645018 0.574198 0.597981 20169\n", "\n", "Classification report for turbine 15, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.042921 0.366120 0.076835 183\n", " 11 0.038168 0.070922 0.049628 282\n", " 12 0.009195 0.031746 0.014260 252\n", " 13 0.017073 0.027778 0.021148 252\n", " 14 0.026465 0.056452 0.036036 248\n", " 15 0.006536 0.004630 0.005420 216\n", " 16 0.014354 0.013889 0.014118 216\n", " 17 0.013423 0.009259 0.010959 216\n", " 18 0.000000 0.000000 0.000000 216\n", " 19 0.831960 0.789108 0.809967 11513\n", " 20 0.920404 0.664791 0.771989 6575\n", "\n", "avg / total 0.776896 0.673211 0.716619 20169\n", "\n", "Classification report for turbine 15, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.444254 0.236098 0.308333 1097\n", " 11 0.131579 0.050274 0.072751 1094\n", " 12 0.073746 0.027747 0.040323 901\n", " 13 0.069231 0.026049 0.037855 691\n", " 14 0.018692 0.006791 0.009963 589\n", " 15 0.034722 0.009862 0.015361 507\n", " 16 0.016529 0.004274 0.006791 468\n", " 17 0.000000 0.000000 0.000000 439\n", " 18 0.020134 0.006944 0.010327 432\n", " 19 0.698520 0.887095 0.781594 10531\n", " 20 0.628468 0.814620 0.709538 3420\n", "\n", "avg / total 0.510491 0.619713 0.553285 20169\n", "\n", "Classification report for turbine 15, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.678466 0.375817 0.483701 1224\n", " 11 0.134048 0.091324 0.108637 1095\n", " 12 0.099042 0.073722 0.084526 841\n", " 13 0.064777 0.022567 0.033473 709\n", " 14 0.028926 0.010671 0.015590 656\n", " 15 0.074074 0.019608 0.031008 612\n", " 16 0.039370 0.009058 0.014728 552\n", " 17 0.020270 0.005758 0.008969 521\n", " 18 0.030769 0.008065 0.012780 496\n", " 19 0.681586 0.859139 0.760132 11167\n", " 20 0.665551 0.865854 0.752603 2296\n", "\n", "avg / total 0.513545 0.607417 0.548889 20169\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 15, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.597537 0.414382 0.489384 2225\n", " 11 0.000000 0.000000 0.000000 216\n", " 12 0.020202 0.011111 0.014337 180\n", " 13 0.023810 0.005556 0.009009 180\n", " 14 0.011765 0.005556 0.007547 180\n", " 15 0.080000 0.024242 0.037209 165\n", " 16 0.015385 0.006944 0.009569 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.877284 0.933835 0.904677 14086\n", " 20 0.455069 0.568064 0.505327 2505\n", "\n", "avg / total 0.736395 0.768903 0.749223 20169\n", "\n", "Classification report for turbine 15, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.003207 0.285714 0.006342 21\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.012500 0.027778 0.017241 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.961506 0.920021 0.940306 13466\n", " 20 0.932707 0.667657 0.778234 6394\n", "\n", "avg / total 0.937671 0.826268 0.874557 20169\n", "\n", "Classification report for turbine 15, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.608456 0.163296 0.257487 2027\n", " 11 0.000000 0.000000 0.000000 189\n", " 12 0.000000 0.000000 0.000000 160\n", " 13 0.000000 0.000000 0.000000 115\n", " 14 0.035714 0.009259 0.014706 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.889286 0.965016 0.925604 12377\n", " 20 0.665941 0.834909 0.740913 4761\n", "\n", "avg / total 0.764264 0.805741 0.768864 20169\n", "\n", "Classification report for turbine 15, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.002532 0.052632 0.004831 19\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.960565 0.948848 0.954670 14838\n", " 20 0.885660 0.837182 0.860739 5024\n", "\n", "avg / total 0.927288 0.906639 0.916746 20169\n", "\n", "Classification report for turbine 15, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.041916 0.070000 0.052434 100\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.951081 0.960598 0.955816 15989\n", " 20 0.890051 0.898687 0.894348 3504\n", "\n", "avg / total 0.908808 0.917993 0.913361 20169\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 15, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.962422 0.965637 0.964027 15569\n", " 20 0.882366 0.872391 0.877350 4600\n", "\n", "avg / total 0.944164 0.944370 0.944258 20169\n", "\n", "Classification report for turbine 15, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.979725 0.979366 0.979546 13667\n", " 20 0.956662 0.957398 0.957030 6502\n", "\n", "avg / total 0.972290 0.972284 0.972287 20169\n", "\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 15, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 8\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.924716 0.983053 0.952993 12982\n", " 20 0.963411 0.890292 0.925409 6891\n", "\n", "avg / total 0.924365 0.936933 0.929582 20169\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 15, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 19 0.968824 0.980966 0.974858 14921\n", " 20 0.947180 0.908918 0.927655 5248\n", "\n", "avg / total 0.963193 0.962219 0.962575 20169\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 15, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 14\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.970889 0.987869 0.979305 16239\n", " 20 0.876099 0.954790 0.913754 3340\n", "\n", "avg / total 0.926791 0.953493 0.939802 20169\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 15, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 31\n", " 11 0.000000 0.000000 0.000000 180\n", " 12 0.000000 0.000000 0.000000 180\n", " 13 0.000000 0.000000 0.000000 180\n", " 14 0.000000 0.000000 0.000000 180\n", " 15 0.000000 0.000000 0.000000 180\n", " 16 0.136364 0.016667 0.029703 180\n", " 17 0.000000 0.000000 0.000000 180\n", " 18 0.000000 0.000000 0.000000 180\n", " 19 0.880636 0.961979 0.919512 14334\n", " 20 0.831304 0.844638 0.837918 4364\n", "\n", "avg / total 0.806951 0.866577 0.835059 20169\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 15, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 6\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.953674 0.953959 0.953816 13401\n", " 20 0.950000 0.936206 0.943053 6474\n", "\n", "avg / total 0.938593 0.934355 0.936458 20169\n", "\n", "Classification report for turbine 15, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 12\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.895220 0.939715 0.916928 12756\n", " 20 0.952213 0.832088 0.888107 6825\n", "\n", "avg / total 0.888407 0.875899 0.880443 20169\n", "\n", "Classification report for turbine 15, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.963286 0.968903 0.966086 14921\n", " 20 0.939735 0.891387 0.914923 5248\n", "\n", "avg / total 0.957158 0.948733 0.952774 20169\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 15, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 6\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.970451 0.968959 0.969704 16269\n", " 20 0.927671 0.938991 0.933297 3606\n", "\n", "avg / total 0.948656 0.949477 0.949060 20169\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 15, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.963094 0.963774 0.963434 15569\n", " 20 0.877097 0.875000 0.876047 4600\n", "\n", "avg / total 0.943480 0.943527 0.943503 20169\n", "\n", "Classification report for turbine 15, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.981719 0.978415 0.980064 13667\n", " 20 0.954948 0.961704 0.958314 6502\n", "\n", "avg / total 0.973089 0.973028 0.973053 20169\n", "\n", "Classification report for turbine 15, turbine category 19.0\n", " precision recall 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0.914100 20169\n", "\n", "Classification report for turbine 15, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.981362 0.978561 0.979960 13667\n", " 20 0.955206 0.960935 0.958062 6502\n", "\n", "avg / total 0.972930 0.972879 0.972900 20169\n", "\n", "Classification report for turbine 15, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.947151 0.984085 0.965265 13258\n", " 20 0.967000 0.894661 0.929425 6911\n", "\n", "avg / total 0.953952 0.953443 0.952984 20169\n", "\n", "Classification report for turbine 15, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 19\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.954159 0.981078 0.967431 14639\n", " 20 0.940786 0.921693 0.931141 5223\n", "\n", "avg / total 0.936172 0.950766 0.943308 20169\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 15, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 19 0.990121 0.987548 0.988833 16543\n", " 20 0.944308 0.953944 0.949101 3626\n", "\n", "avg / total 0.981885 0.981506 0.981690 20169\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 16, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 19 0.928557 0.994948 0.960607 18210\n", " 20 0.959184 0.607987 0.744234 3556\n", "\n", "avg / total 0.933560 0.931728 0.925257 21766\n", "\n", "Classification report for turbine 16, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 273\n", " 11 0.000000 0.000000 0.000000 301\n", " 12 0.000000 0.000000 0.000000 279\n", " 13 0.000000 0.000000 0.000000 252\n", " 14 0.000000 0.000000 0.000000 252\n", " 15 0.000000 0.000000 0.000000 192\n", " 16 0.000000 0.000000 0.000000 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.878749 0.984712 0.928718 17465\n", " 20 0.736674 0.696983 0.716279 2320\n", "\n", "avg / total 0.783628 0.864422 0.821549 21766\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 16, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 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0.985165 0.980821 0.982988 18145\n", " 20 0.939241 0.922121 0.930602 3621\n", "\n", "avg / total 0.977525 0.971056 0.974273 21766\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 16, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.993496 0.991143 0.992318 21113\n", " 20 0.859060 0.784074 0.819856 653\n", "\n", "avg / total 0.989463 0.984931 0.987144 21766\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 16, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 19 0.947070 0.991433 0.968744 18210\n", " 20 0.942286 0.716254 0.813868 3556\n", "\n", "avg / total 0.946289 0.946476 0.943441 21766\n", "\n", "Classification report for turbine 16, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 19 0.955891 0.983539 0.969518 19015\n", " 20 0.857792 0.686296 0.762520 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0.000000 0.000000 0.000000 36\n", " 14 0.025641 0.333333 0.047619 3\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.990939 0.989287 0.990112 21003\n", " 20 0.858824 0.788580 0.822204 648\n", "\n", "avg / total 0.981773 0.978131 0.979889 21766\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 16, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 19 0.928828 0.994728 0.960649 18210\n", " 20 0.957597 0.609674 0.745017 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"Classification report for turbine 16, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.994315 0.985885 0.990083 21113\n", " 20 0.863487 0.803982 0.832672 653\n", "\n", "avg / total 0.990390 0.980428 0.985360 21766\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 16, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.843913 0.673588 0.749192 2408\n", " 11 0.006803 0.004637 0.005515 647\n", " 12 0.000000 0.000000 0.000000 605\n", " 13 0.000000 0.000000 0.000000 576\n", " 14 0.045455 0.003663 0.006780 546\n", " 15 0.000000 0.000000 0.000000 511\n", " 16 0.018182 0.001984 0.003578 504\n", " 17 0.040000 0.001984 0.003781 504\n", " 18 0.000000 0.000000 0.000000 422\n", " 19 0.703462 0.953303 0.809544 13898\n", " 20 0.240283 0.059389 0.095238 1145\n", "\n", "avg / total 0.557866 0.686667 0.605308 21766\n", "\n", "Classification report for turbine 16, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.529080 0.851257 0.652570 1432\n", " 11 0.071072 0.087289 0.078351 653\n", " 12 0.020134 0.009804 0.013187 612\n", " 13 0.019608 0.011438 0.014448 612\n", " 14 0.017921 0.008170 0.011223 612\n", " 15 0.013369 0.008651 0.010504 578\n", " 16 0.024631 0.008681 0.012837 576\n", " 17 0.017857 0.005566 0.008487 539\n", " 18 0.036649 0.014957 0.021244 468\n", " 19 0.749692 0.845951 0.794918 14385\n", " 20 0.616487 0.264819 0.370490 1299\n", "\n", "avg / total 0.573058 0.635257 0.595128 21766\n", "\n", "Classification report for turbine 16, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.026380 0.941935 0.051323 310\n", " 11 0.001916 0.013889 0.003367 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 75\n", " 16 0.002710 0.009259 0.004193 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.880444 0.738444 0.803217 8048\n", " 20 0.887070 0.170427 0.285922 12721\n", "\n", "avg / total 0.844383 0.386153 0.464858 21766\n", "\n", "Classification report for turbine 16, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.228690 0.571429 0.326652 385\n", " 11 0.008197 0.001866 0.003040 536\n", " 12 0.018868 0.003968 0.006557 504\n", " 13 0.015038 0.003968 0.006279 504\n", " 14 0.048544 0.010163 0.016807 492\n", " 15 0.043478 0.015054 0.022364 465\n", " 16 0.036496 0.011876 0.017921 421\n", " 17 0.009901 0.004651 0.006329 430\n", " 18 0.029412 0.010101 0.015038 396\n", " 19 0.787811 0.928903 0.852559 14445\n", " 20 0.895958 0.750941 0.817065 3188\n", "\n", "avg / total 0.662554 0.737848 0.693226 21766\n", "\n", "Classification report for turbine 16, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.776271 0.579747 0.663768 395\n", " 11 0.023529 0.009449 0.013483 635\n", " 12 0.010526 0.003268 0.004988 612\n", " 13 0.013699 0.005515 0.007864 544\n", " 14 0.006623 0.001946 0.003008 514\n", " 15 0.012121 0.003968 0.005979 504\n", " 16 0.036458 0.014056 0.020290 498\n", " 17 0.005988 0.002137 0.003150 468\n", " 18 0.000000 0.000000 0.000000 444\n", " 19 0.795001 0.924987 0.855082 16917\n", " 20 0.327217 0.455319 0.380783 235\n", "\n", "avg / total 0.638237 0.735367 0.682216 21766\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 16, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.936124 0.994728 0.964537 18210\n", " 20 0.960265 0.652418 0.776959 3556\n", "\n", "avg / total 0.940068 0.938804 0.933891 21766\n", "\n", "Classification report for turbine 16, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 4\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.943594 0.985092 0.963897 18782\n", " 20 0.844300 0.676820 0.751340 2692\n", "\n", "avg / total 0.918655 0.933750 0.924677 21766\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 16, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 79\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.870339 0.941746 0.904636 8154\n", " 20 0.938381 0.935556 0.936966 12957\n", "\n", "avg / total 0.884652 0.909722 0.896659 21766\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 16, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.986403 0.983522 0.984960 18145\n", " 20 0.935314 0.930406 0.932853 3621\n", "\n", "avg / total 0.977904 0.974685 0.976292 21766\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 16, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.994843 0.995974 0.995408 21113\n", " 20 0.887070 0.830015 0.857595 653\n", "\n", "avg / total 0.991610 0.990995 0.991274 21766\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 16, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 45\n", " 11 0.062500 0.003968 0.007463 252\n", " 12 0.022388 0.011905 0.015544 252\n", " 13 0.011976 0.007937 0.009547 252\n", " 14 0.000000 0.000000 0.000000 252\n", " 15 0.000000 0.000000 0.000000 252\n", " 16 0.000000 0.000000 0.000000 252\n", " 17 0.250000 0.003968 0.007812 252\n", " 18 0.000000 0.000000 0.000000 236\n", " 19 0.851273 0.982583 0.912227 16363\n", " 20 0.953627 0.716498 0.818228 3358\n", "\n", "avg / total 0.791100 0.849536 0.812485 21766\n", "\n", "Classification report for turbine 16, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.016949 0.050000 0.025316 20\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.916036 0.957386 0.936255 18210\n", " 20 0.836641 0.678518 0.749328 2672\n", "\n", "avg / total 0.869101 0.884315 0.875306 21766\n", "\n", "Classification report for turbine 16, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 5\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.037037 0.027778 0.031746 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.095238 1.000000 0.173913 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.916013 0.854879 0.884391 8331\n", " 20 0.938573 0.940572 0.939571 13142\n", "\n", "avg / total 0.917522 0.896812 0.906143 21766\n", "\n", "Classification report for turbine 16, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 18\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.041667 0.009259 0.015152 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.942700 0.977651 0.959857 17316\n", " 20 0.934081 0.933296 0.933688 3568\n", "\n", "avg / total 0.903294 0.930810 0.916747 21766\n", "\n", "Classification report for turbine 16, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 1.000000 0.083333 0.153846 12\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.090909 0.013889 0.024096 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.038462 0.013889 0.020408 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.967822 0.983983 0.975836 20541\n", " 20 0.855738 0.819466 0.837209 637\n", "\n", "avg / total 0.939376 0.952724 0.945649 21766\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 16, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.930576 0.994454 0.961455 18210\n", " 20 0.956201 0.620079 0.752303 3556\n", "\n", "avg / total 0.934762 0.933290 0.927285 21766\n", "\n", "Classification report for turbine 16, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.957325 0.983907 0.970434 19015\n", " 20 0.862348 0.696838 0.770808 2751\n", "\n", "avg / total 0.945321 0.947625 0.945203 21766\n", "\n", "Classification report for turbine 16, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.914727 0.936416 0.925444 8477\n", " 20 0.958817 0.944315 0.951511 13289\n", "\n", "avg / total 0.941646 0.941239 0.941359 21766\n", "\n", "Classification report for turbine 16, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 1487\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 64\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.962481 0.987154 0.974661 17671\n", " 20 0.558210 0.915766 0.693620 2220\n", "\n", "avg / total 0.838336 0.894836 0.862036 21766\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 16, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.995162 0.993795 0.994478 21113\n", " 20 0.904132 0.837672 0.869634 653\n", "\n", "avg / total 0.992431 0.989111 0.990733 21766\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 16, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.922117 0.994124 0.956768 18210\n", " 20 0.949859 0.570022 0.712478 3556\n", "\n", "avg / total 0.926649 0.924837 0.916857 21766\n", "\n", "Classification report for turbine 16, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.960795 0.983382 0.971957 19015\n", " 20 0.862847 0.722646 0.786548 2751\n", "\n", "avg / total 0.948416 0.950427 0.948523 21766\n", "\n", "Classification report for turbine 16, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.933712 0.950454 0.942009 8477\n", " 20 0.968029 0.956957 0.962461 13289\n", "\n", "avg / total 0.954664 0.954424 0.954496 21766\n", "\n", "Classification report for turbine 16, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 84\n", " 11 0.000000 0.000000 0.000000 118\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 102\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 43\n", " 19 0.952226 0.988729 0.970134 17478\n", " 20 0.920951 0.939915 0.930336 3545\n", "\n", "avg / total 0.914627 0.947027 0.930536 21766\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 16, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 13\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.980863 0.994477 0.987623 20822\n", " 20 0.860697 0.807154 0.833066 643\n", "\n", "avg / total 0.963749 0.975191 0.969400 21766\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 17, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 9\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.972018 0.975364 0.973688 18591\n", " 20 0.823471 0.892613 0.856649 2775\n", "\n", "avg / total 0.939663 0.951392 0.945347 21663\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 17, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.117647 0.011561 0.021053 173\n", " 11 0.000000 0.000000 0.000000 144\n", " 12 0.000000 0.000000 0.000000 144\n", " 13 0.000000 0.000000 0.000000 113\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 88\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.904522 0.972426 0.937246 15159\n", " 20 0.895344 0.851819 0.873039 5554\n", "\n", "avg / total 0.863442 0.898952 0.879851 21663\n", "\n", "Classification report for turbine 17, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.046272 0.081081 0.058920 222\n", " 11 0.032258 0.005102 0.008811 196\n", " 12 0.037037 0.007299 0.012195 137\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 105\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.879292 0.934274 0.905949 10635\n", " 20 0.941342 0.914242 0.927594 9900\n", "\n", "avg / total 0.862864 0.877395 0.869429 21663\n", "\n", "Classification report for turbine 17, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.303571 0.049708 0.085427 342\n", " 11 0.000000 0.000000 0.000000 261\n", " 12 0.012987 0.004630 0.006826 216\n", " 13 0.000000 0.000000 0.000000 216\n", " 14 0.000000 0.000000 0.000000 216\n", " 15 0.000000 0.000000 0.000000 216\n", " 16 0.000000 0.000000 0.000000 222\n", " 17 0.000000 0.000000 0.000000 252\n", " 18 0.000000 0.000000 0.000000 252\n", " 19 0.904520 0.979201 0.940380 17453\n", " 20 0.709782 0.870600 0.782008 2017\n", "\n", "avg / total 0.799743 0.870794 0.831854 21663\n", "\n", "Classification report for turbine 17, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.100000 0.084337 0.091503 83\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 66\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.963360 0.974439 0.968868 18348\n", " 20 0.917068 0.905999 0.911500 2734\n", "\n", "avg / total 0.932064 0.939990 0.935993 21663\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 17, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 19 0.985977 0.979321 0.982638 18811\n", " 20 0.869419 0.908135 0.888355 2852\n", "\n", "avg / total 0.970632 0.969949 0.970225 21663\n", "\n", "Classification report for turbine 17, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 19 0.946799 0.973039 0.959740 15912\n", " 20 0.919209 0.848722 0.882560 5751\n", "\n", "avg / total 0.939474 0.940036 0.939250 21663\n", "\n", "Classification report for turbine 17, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 19 0.902453 0.983953 0.941442 11217\n", " 20 0.980918 0.885794 0.930932 10446\n", "\n", "avg / total 0.940289 0.936620 0.936374 21663\n", "\n", "Classification report for turbine 17, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 5\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 35\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.979269 0.987950 0.983590 18838\n", " 20 0.901053 0.945519 0.922751 2533\n", "\n", "avg / total 0.956923 0.969672 0.963218 21663\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 17, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.992796 0.978488 0.985590 18873\n", " 20 0.936794 0.950896 0.943792 2790\n", "\n", "avg / total 0.985583 0.974934 0.980207 21663\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 17, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.983311 0.977247 0.980270 18811\n", " 20 0.855795 0.890603 0.872852 2852\n", "\n", "avg / total 0.966523 0.965840 0.966128 21663\n", "\n", "Classification report for turbine 17, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.946466 0.977753 0.961855 15912\n", " 20 0.932249 0.846983 0.887573 5751\n", "\n", "avg / total 0.942691 0.943037 0.942135 21663\n", "\n", "Classification report for turbine 17, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.896425 0.981457 0.937016 11217\n", " 20 0.977830 0.878231 0.925358 10446\n", "\n", "avg / total 0.935679 0.931681 0.931394 21663\n", "\n", "Classification report for turbine 17, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.991429 0.987690 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"\n", "avg / total 0.934595 0.933712 0.932825 21663\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 17, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.051724 0.034884 0.041667 86\n", " 11 0.000000 0.000000 0.000000 41\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.946710 0.971677 0.959031 15888\n", " 20 0.856218 0.833210 0.844557 5396\n", "\n", "avg / total 0.907812 0.920325 0.913904 21663\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 17, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 38\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.860569 0.982565 0.917530 10955\n", " 20 0.973235 0.851088 0.908073 10382\n", "\n", "avg / total 0.901614 0.904768 0.899190 21663\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 17, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 5\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.975438 0.984532 0.979964 18878\n", " 20 0.878000 0.880819 0.879407 2492\n", "\n", "avg / total 0.951036 0.959285 0.955142 21663\n", "\n", "Classification report for turbine 17, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.122340 0.169118 0.141975 136\n", " 11 0.000000 0.000000 0.000000 57\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.978043 0.988370 0.983179 18658\n", " 20 0.849568 0.844922 0.847239 2560\n", "\n", "avg / total 0.943538 0.952177 0.947809 21663\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 17, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.982648 0.981447 0.982047 18811\n", " 20 0.878831 0.874825 0.876823 2852\n", "\n", "avg / total 0.968981 0.967410 0.968194 21663\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 17, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 4\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.939586 0.969930 0.954517 15730\n", " 20 0.892911 0.843999 0.867766 5641\n", "\n", "avg / total 0.914767 0.924064 0.919061 21663\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 17, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.923986 0.982883 0.952525 11217\n", " 20 0.980511 0.910301 0.944102 10446\n", "\n", "avg / total 0.951243 0.947883 0.948464 21663\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 17, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.988510 0.986957 0.987733 19090\n", " 20 0.910818 0.912942 0.911879 2573\n", "\n", "avg / total 0.979282 0.978166 0.978723 21663\n", "\n" ] }, { 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"\n", "avg / total 0.965321 0.960855 0.963061 21663\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 17, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 19 0.935857 0.971028 0.953118 15912\n", " 20 0.921445 0.815858 0.865443 5751\n", "\n", "avg / total 0.932031 0.929834 0.929843 21663\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program 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"Classification report for turbine 17, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.989080 0.986852 0.987964 19090\n", " 20 0.911017 0.919161 0.915071 2573\n", "\n", "avg / total 0.979808 0.978812 0.979307 21663\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 17, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 865\n", " 11 0.000000 0.000000 0.000000 822\n", " 12 0.000000 0.000000 0.000000 362\n", " 13 0.000000 0.000000 0.000000 256\n", " 14 0.000000 0.000000 0.000000 185\n", " 15 0.000000 0.000000 0.000000 180\n", " 16 0.000000 0.000000 0.000000 180\n", " 17 0.000000 0.000000 0.000000 180\n", " 18 0.000000 0.000000 0.000000 173\n", " 19 0.871319 0.988721 0.926315 16580\n", " 20 0.625922 0.947872 0.753967 1880\n", "\n", "avg / total 0.721193 0.838988 0.774397 21663\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 17, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.118998 0.619565 0.199650 92\n", " 11 0.012500 0.006944 0.008929 144\n", " 12 0.000000 0.000000 0.000000 144\n", " 13 0.000000 0.000000 0.000000 144\n", " 14 0.000000 0.000000 0.000000 144\n", " 15 0.000000 0.000000 0.000000 144\n", " 16 0.000000 0.000000 0.000000 144\n", " 17 0.007740 0.069444 0.013928 144\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.927895 0.853018 0.888882 17907\n", " 20 0.743893 0.751592 0.747723 2512\n", "\n", "avg / total 0.853914 0.795412 0.822469 21663\n", "\n", "Classification report for turbine 17, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.669774 0.387072 0.490612 2599\n", " 11 0.000000 0.000000 0.000000 1049\n", " 12 0.016949 0.001140 0.002137 877\n", " 13 0.000000 0.000000 0.000000 825\n", " 14 0.013699 0.001332 0.002427 751\n", " 15 0.000000 0.000000 0.000000 618\n", " 16 0.000000 0.000000 0.000000 504\n", " 17 0.008547 0.003992 0.005442 501\n", " 18 0.000000 0.000000 0.000000 448\n", " 19 0.670967 0.933144 0.780630 10590\n", " 20 0.440909 0.735608 0.551350 2901\n", "\n", "avg / total 0.468762 0.601302 0.514604 21663\n", "\n", "Classification report for turbine 17, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.046827 0.352941 0.082684 391\n", " 11 0.004587 0.013333 0.006826 150\n", " 12 0.002299 0.009259 0.003683 108\n", " 13 0.015152 0.009259 0.011494 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.003876 0.009259 0.005464 108\n", " 17 0.003311 0.009259 0.004878 108\n", " 18 0.004444 0.009259 0.006006 108\n", " 19 0.880052 0.872899 0.876461 10826\n", " 20 0.890072 0.561006 0.688227 9540\n", "\n", "avg / total 0.832796 0.689978 0.742788 21663\n", "\n", "Classification report for turbine 17, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.241199 0.616667 0.346767 300\n", " 11 0.022727 0.011111 0.014925 270\n", " 12 0.010417 0.007752 0.008889 129\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.011364 0.009524 0.010363 105\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.014706 0.018519 0.016393 108\n", " 17 0.007353 0.009259 0.008197 108\n", " 18 0.012048 0.009259 0.010471 108\n", " 19 0.940416 0.944662 0.942534 18161\n", " 20 0.754891 0.607970 0.673511 2158\n", "\n", "avg / total 0.867500 0.861469 0.862525 21663\n", "\n", "Classification report for turbine 17, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.007752 0.061538 0.013769 65\n", " 11 0.013333 0.003968 0.006116 252\n", " 12 0.014493 0.003968 0.006231 252\n", " 13 0.018692 0.007937 0.011142 252\n", " 14 0.015873 0.003968 0.006349 252\n", " 15 0.000000 0.000000 0.000000 252\n", " 16 0.000000 0.000000 0.000000 252\n", " 17 0.000000 0.000000 0.000000 252\n", " 18 0.000000 0.000000 0.000000 252\n", " 19 0.895007 0.959998 0.926364 17049\n", " 20 0.820714 0.744572 0.780791 2533\n", "\n", "avg / total 0.801093 0.843004 0.820742 21663\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 17, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 86\n", " 11 0.000000 0.000000 0.000000 82\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.969846 0.978689 0.974247 18535\n", " 20 0.820210 0.896233 0.856538 2708\n", "\n", "avg / total 0.932337 0.949407 0.940644 21663\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 17, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.947323 0.960659 0.953944 15912\n", " 20 0.926409 0.840549 0.881393 5751\n", "\n", "avg / total 0.941771 0.928773 0.934684 21663\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 17, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.914787 0.961844 0.937725 11217\n", " 20 0.981759 0.901685 0.940020 10446\n", "\n", "avg / total 0.947082 0.932835 0.938832 21663\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 17, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 12\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 35\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.975616 0.987631 0.981587 18838\n", " 20 0.897059 0.917656 0.907241 2526\n", "\n", "avg / total 0.952990 0.965840 0.959370 21663\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 17, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.992470 0.977746 0.985053 18873\n", " 20 0.929751 0.948746 0.939152 2790\n", "\n", "avg / total 0.984393 0.974011 0.979141 21663\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 17, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.007299 0.005051 0.005970 198\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.093023 0.055556 0.069565 72\n", " 17 0.023256 0.013889 0.017391 72\n", " 18 0.009259 0.013889 0.011111 72\n", " 19 0.953170 0.933373 0.943168 18296\n", " 20 0.787679 0.828384 0.807519 2593\n", "\n", "avg / total 0.899789 0.887781 0.893613 21663\n", "\n", "Classification report for turbine 17, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.104878 0.231183 0.144295 186\n", " 11 0.000000 0.000000 0.000000 154\n", " 12 0.000000 0.000000 0.000000 130\n", " 13 0.000000 0.000000 0.000000 90\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.891716 0.910200 0.900863 15245\n", " 20 0.897159 0.787013 0.838485 5498\n", "\n", "avg / total 0.856128 0.842266 0.848012 21663\n", "\n", "Classification report for turbine 17, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 131\n", " 11 0.000000 0.000000 0.000000 144\n", " 12 0.000000 0.000000 0.000000 144\n", " 13 0.000000 0.000000 0.000000 144\n", " 14 0.000000 0.000000 0.000000 144\n", " 15 0.000000 0.000000 0.000000 144\n", " 16 0.250000 0.006944 0.013514 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.820085 0.948819 0.879767 10199\n", " 20 0.953486 0.875847 0.913019 10181\n", "\n", "avg / total 0.835871 0.858376 0.843380 21663\n", "\n", "Classification report for turbine 17, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.561728 0.061486 0.110840 1480\n", " 11 0.052632 0.003181 0.006000 943\n", " 12 0.046512 0.003236 0.006051 618\n", " 13 0.033333 0.001980 0.003738 505\n", " 14 0.027778 0.002315 0.004274 432\n", " 15 0.000000 0.000000 0.000000 432\n", " 16 0.000000 0.000000 0.000000 413\n", " 17 0.000000 0.000000 0.000000 396\n", " 18 0.000000 0.000000 0.000000 396\n", " 19 0.785116 0.972382 0.868772 15135\n", " 20 0.293040 0.788609 0.427300 913\n", "\n", "avg / total 0.604203 0.717121 0.633161 21663\n", "\n", "Classification report for turbine 17, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.035865 0.062271 0.045515 273\n", " 11 0.114379 0.086420 0.098453 405\n", " 12 0.062350 0.065657 0.063961 396\n", " 13 0.055794 0.035422 0.043333 367\n", " 14 0.072917 0.038889 0.050725 360\n", " 15 0.026178 0.013889 0.018149 360\n", " 16 0.029126 0.008333 0.012959 360\n", " 17 0.011905 0.003067 0.004878 326\n", " 18 0.000000 0.000000 0.000000 324\n", " 19 0.866033 0.914247 0.889487 16256\n", " 20 0.748665 0.815295 0.780561 2236\n", "\n", "avg / total 0.734136 0.775470 0.753793 21663\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 17, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.626271 0.563692 0.593336 1311\n", " 11 0.018657 0.020243 0.019417 494\n", " 12 0.062880 0.067834 0.065263 457\n", " 13 0.030812 0.050926 0.038394 432\n", " 14 0.002849 0.002732 0.002789 366\n", " 15 0.000000 0.000000 0.000000 304\n", " 16 0.002049 0.003472 0.002577 288\n", " 17 0.039548 0.024306 0.030108 288\n", " 18 0.003717 0.003472 0.003591 288\n", " 19 0.858653 0.823464 0.840690 16178\n", " 20 0.529654 0.717582 0.609459 1257\n", "\n", "avg / total 0.712896 0.694087 0.702216 21663\n", "\n", "Classification report for turbine 17, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.445062 0.672400 0.535606 2500\n", " 11 0.061972 0.020755 0.031095 1060\n", " 12 0.057895 0.011690 0.019452 941\n", " 13 0.027079 0.016018 0.020129 874\n", " 14 0.017241 0.003807 0.006237 788\n", " 15 0.001570 0.001639 0.001604 610\n", " 16 0.083333 0.019097 0.031073 576\n", " 17 0.041667 0.006944 0.011905 576\n", " 18 0.020761 0.010929 0.014320 549\n", " 19 0.667603 0.843787 0.745426 10985\n", " 20 0.410050 0.299909 0.346436 2204\n", "\n", "avg / total 0.442773 0.539307 0.480009 21663\n", "\n", "Classification report for turbine 17, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.146655 0.459746 0.222374 1416\n", " 11 0.006410 0.012945 0.008574 618\n", " 12 0.035294 0.019272 0.024931 467\n", " 13 0.025510 0.028818 0.027064 347\n", " 14 0.025090 0.043210 0.031746 324\n", " 15 0.025862 0.018519 0.021583 324\n", " 16 0.000000 0.000000 0.000000 324\n", " 17 0.005988 0.006173 0.006079 324\n", " 18 0.005848 0.003086 0.004040 324\n", " 19 0.705696 0.828518 0.762191 8584\n", " 20 0.787481 0.355011 0.489394 8611\n", "\n", "avg / total 0.604533 0.501777 0.513252 21663\n", "\n", "Classification report for turbine 17, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.079515 0.662921 0.141998 178\n", " 11 0.004754 0.024194 0.007947 124\n", " 12 0.006608 0.027778 0.010676 108\n", " 13 0.002646 0.009259 0.004115 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.009804 0.018519 0.012821 108\n", " 16 0.000000 0.000000 0.000000 99\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.944666 0.859268 0.899945 18219\n", " 20 0.831237 0.321443 0.463607 2467\n", "\n", "avg / total 0.889920 0.765129 0.811017 21663\n", "\n", "Classification report for turbine 17, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 4\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.015152 0.027778 0.019608 36\n", " 19 0.976971 0.928679 0.952213 18592\n", " 20 0.882961 0.583663 0.702773 2779\n", "\n", "avg / total 0.951767 0.871948 0.907411 21663\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 17, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.986089 0.975972 0.981004 18811\n", " 20 0.851560 0.909187 0.879430 2852\n", "\n", "avg / total 0.968378 0.967179 0.967632 21663\n", "\n", "Classification report for turbine 17, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 111\n", " 11 0.000000 0.000000 0.000000 38\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.936450 0.975956 0.955795 15763\n", " 20 0.886724 0.844153 0.864915 5499\n", "\n", "avg / total 0.906493 0.924433 0.915033 21663\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 17, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 19 0.882363 0.961576 0.920268 11217\n", " 20 0.981439 0.855447 0.914122 10446\n", "\n", "avg / total 0.930138 0.910400 0.917304 21663\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 17, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.989968 0.982190 0.986064 19090\n", " 20 0.905380 0.922270 0.913747 2573\n", "\n", "avg / total 0.979921 0.975073 0.977474 21663\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 17, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 7\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.981808 0.981177 0.981492 18647\n", " 20 0.908581 0.953326 0.930416 2721\n", "\n", "avg / total 0.959241 0.964317 0.961711 21663\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 17, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 50\n", " 11 0.000000 0.000000 0.000000 288\n", " 12 0.000000 0.000000 0.000000 288\n", " 13 0.000000 0.000000 0.000000 288\n", " 14 0.000000 0.000000 0.000000 288\n", " 15 0.000000 0.000000 0.000000 288\n", " 16 0.000000 0.000000 0.000000 288\n", " 17 0.000000 0.000000 0.000000 288\n", " 18 0.000000 0.000000 0.000000 288\n", " 19 0.885834 0.977267 0.929307 16848\n", " 20 0.738947 0.923608 0.821022 2461\n", "\n", "avg / total 0.772888 0.864977 0.816023 21663\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 17, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.090909 0.166667 0.117647 12\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.001541 0.013889 0.002774 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.909524 0.902806 0.906152 15433\n", " 20 0.903238 0.815668 0.857223 5642\n", "\n", "avg / total 0.883255 0.855745 0.868888 21663\n", "\n", "Classification report for turbine 17, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.005882 0.090909 0.011050 11\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.003817 0.013889 0.005988 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.895183 0.928611 0.911590 10926\n", " 20 0.946045 0.889655 0.916984 10150\n", "\n", "avg / total 0.894773 0.885288 0.889442 21663\n", "\n", "Classification report for turbine 17, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.250000 0.076923 0.117647 13\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.955835 0.976838 0.966223 18522\n", " 20 0.902262 0.875392 0.888624 2552\n", "\n", "avg / total 0.923685 0.938374 0.930881 21663\n", "\n", "Classification report for turbine 17, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 13\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.165714 0.402778 0.234818 72\n", " 16 0.071429 0.013889 0.023256 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.964392 0.977984 0.971140 18305\n", " 20 0.926005 0.940051 0.932975 2769\n", "\n", "avg / total 0.934052 0.947930 0.940715 21663\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 17, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.983653 0.975653 0.979636 18811\n", " 20 0.847587 0.893058 0.869729 2852\n", "\n", "avg / total 0.965740 0.964779 0.965167 21663\n", "\n", "Classification report for turbine 17, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.943479 0.978758 0.960795 15912\n", " 20 0.934445 0.837767 0.883469 5751\n", "\n", "avg / total 0.941080 0.941329 0.940267 21663\n", "\n", "Classification report for turbine 17, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.924740 0.983685 0.953303 11217\n", " 20 0.981194 0.914034 0.946424 10446\n", "\n", "avg / total 0.951963 0.950099 0.949986 21663\n", "\n", "Classification report for turbine 17, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.991904 0.988318 0.990108 19090\n", " 20 0.915594 0.940148 0.927709 2573\n", "\n", "avg / total 0.982840 0.982597 0.982696 21663\n", "\n", "Classification report for turbine 17, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.993621 0.990357 0.991986 18873\n", " 20 0.936185 0.956989 0.946473 2790\n", "\n", "avg / total 0.986224 0.986059 0.986124 21663\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 17, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.986065 0.978045 0.982038 18811\n", " 20 0.862562 0.908836 0.885095 2852\n", "\n", "avg / total 0.969805 0.968933 0.969276 21663\n", "\n", "Classification report for turbine 17, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.944272 0.975427 0.959597 15912\n", " 20 0.925182 0.840723 0.880933 5751\n", "\n", "avg / total 0.939204 0.939667 0.938714 21663\n", "\n", "Classification report for turbine 17, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 21\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.887161 0.983401 0.932806 11025\n", " 20 0.972463 0.888953 0.928835 10329\n", "\n", "avg / total 0.915179 0.924341 0.917607 21663\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 17, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 20\n", " 11 0.000000 0.000000 0.000000 39\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.973715 0.987338 0.980479 18797\n", " 20 0.907895 0.918200 0.913018 2555\n", "\n", "avg / total 0.951973 0.965009 0.958447 21663\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 17, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.989972 0.983362 0.986656 18873\n", " 20 0.929260 0.932258 0.930757 2790\n", "\n", "avg / total 0.982153 0.976781 0.979457 21663\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 18, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 19 0.985247 0.996116 0.990652 19309\n", " 20 0.959634 0.860937 0.907610 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"C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 18, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.987213 0.989136 0.988173 20527\n", " 20 0.860088 0.684642 0.762402 853\n", "\n", "avg / total 0.982141 0.976988 0.979166 21380\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program 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"stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 18, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.182171 0.415929 0.253369 113\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.005435 0.009259 0.006849 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.006849 0.009259 0.007874 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.935368 0.944297 0.939811 18437\n", " 20 0.917734 0.692269 0.789214 1966\n", "\n", "avg / total 0.892028 0.880262 0.884430 21380\n", "\n", "Classification report for turbine 18, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 98\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.959138 0.968887 0.963988 19381\n", " 20 0.836115 0.831698 0.833901 1325\n", "\n", "avg / total 0.921277 0.929841 0.925536 21380\n", "\n", "Classification report for turbine 18, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.016529 0.062500 0.026144 32\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.905480 0.980604 0.941546 17272\n", " 20 0.969163 0.684932 0.802627 3212\n", "\n", "avg / total 0.877125 0.895182 0.881256 21380\n", "\n", "Classification report for turbine 18, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.987259 0.981439 0.984340 20527\n", " 20 0.866878 0.641266 0.737197 853\n", "\n", "avg / total 0.982456 0.967867 0.974480 21380\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 18, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.983509 0.986021 0.984763 15666\n", " 20 0.986073 0.941722 0.963387 5714\n", "\n", "avg / total 0.984195 0.974181 0.979051 21380\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 18, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.984841 0.995909 0.990344 19309\n", " 20 0.957389 0.857074 0.904459 2071\n", "\n", "avg / total 0.982182 0.982460 0.982024 21380\n", "\n", "Classification report for turbine 18, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.991860 0.991959 0.991910 20023\n", " 20 0.881181 0.879882 0.880531 1357\n", "\n", "avg / total 0.984835 0.984846 0.984840 21380\n", "\n", "Classification report for turbine 18, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.963180 0.995313 0.978983 18135\n", " 20 0.967803 0.787365 0.868309 3245\n", "\n", "avg / total 0.963882 0.963751 0.962185 21380\n", "\n", "Classification report for turbine 18, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.988245 0.995226 0.991723 20527\n", " 20 0.861582 0.715123 0.781550 853\n", "\n", "avg / total 0.983191 0.984051 0.983338 21380\n", "\n", "Classification report for turbine 18, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.987285 0.996234 0.991739 15666\n", " 20 0.989411 0.964823 0.976963 5714\n", "\n", "avg / total 0.987853 0.987839 0.987790 21380\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 18, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.020270 0.013043 0.015873 230\n", " 11 0.000000 0.000000 0.000000 107\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.027778 0.013889 0.018519 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.942894 0.981534 0.961826 18521\n", " 20 0.926742 0.771060 0.841764 2018\n", "\n", "avg / total 0.904592 0.923246 0.912893 21380\n", "\n", "Classification report for turbine 18, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.272059 0.330357 0.298387 112\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.031250 0.027778 0.029412 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.959140 0.967271 0.963188 19463\n", " 20 0.794068 0.762408 0.777916 1229\n", "\n", "avg / total 0.920317 0.926193 0.923205 21380\n", "\n", "Classification report for turbine 18, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 6\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.943721 0.977544 0.960334 17857\n", " 20 0.970020 0.761536 0.853227 3229\n", "\n", "avg / total 0.934715 0.931478 0.930952 21380\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 18, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.168831 0.166667 0.167742 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with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 18, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.990527 0.971333 0.980836 20023\n", " 20 0.898637 0.777450 0.833663 1357\n", "\n", "avg / total 0.984695 0.959027 0.971495 21380\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true 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0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.967819 0.991313 0.979425 20144\n", " 20 0.819728 0.584951 0.682720 824\n", "\n", "avg / total 0.943461 0.956548 0.949116 21380\n", "\n", "Classification report for turbine 18, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 19 0.978246 0.993170 0.985651 15666\n", " 20 0.988495 0.932272 0.959560 5714\n", "\n", "avg / total 0.980985 0.976894 0.978678 21380\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", 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precision recall f1-score support\n", "\n", " 13 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.984902 0.995213 0.990030 15666\n", " 20 0.988803 0.958173 0.973247 5714\n", "\n", "avg / total 0.985945 0.985313 0.985545 21380\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 18, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 2642\n", " 11 0.000000 0.000000 0.000000 78\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 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0.000000 0.000000 0.000000 0\n", " 19 0.984484 0.946398 0.965066 19309\n", " 20 0.969767 0.805408 0.879979 2071\n", "\n", "avg / total 0.983059 0.932741 0.956824 21380\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 18, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 19 0.990010 0.979923 0.984941 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samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 18, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.023256 0.010989 0.014925 91\n", " 11 0.000000 0.000000 0.000000 146\n", " 12 0.000000 0.000000 0.000000 144\n", " 13 0.031250 0.006944 0.011364 144\n", " 14 0.062500 0.022388 0.032967 134\n", " 15 0.026786 0.027778 0.027273 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.931244 0.972219 0.951291 18250\n", " 20 0.948857 0.773418 0.852202 2039\n", "\n", "avg / total 0.886240 0.904022 0.893782 21380\n", "\n", "Classification report for turbine 18, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.018519 0.062500 0.028571 16\n", " 11 0.000000 0.000000 0.000000 144\n", " 12 0.000000 0.000000 0.000000 144\n", " 13 0.000000 0.000000 0.000000 144\n", " 14 0.000000 0.000000 0.000000 144\n", " 15 0.000000 0.000000 0.000000 144\n", " 16 0.000000 0.000000 0.000000 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.932760 0.970912 0.951454 18874\n", " 20 0.865399 0.850523 0.857897 1338\n", "\n", "avg / total 0.877601 0.910384 0.893642 21380\n", "\n", "Classification report for turbine 18, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 19\n", " 11 0.066667 0.006944 0.012579 144\n", " 12 0.000000 0.000000 0.000000 144\n", " 13 0.000000 0.000000 0.000000 167\n", " 14 0.000000 0.000000 0.000000 180\n", " 15 0.000000 0.000000 0.000000 180\n", " 16 0.000000 0.000000 0.000000 180\n", " 17 0.000000 0.000000 0.000000 180\n", " 18 0.000000 0.000000 0.000000 180\n", " 19 0.891335 0.969165 0.928622 16961\n", " 20 0.924203 0.704762 0.799702 3045\n", "\n", "avg / total 0.839183 0.869270 0.850667 21380\n", "\n", "Classification report for turbine 18, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.276596 0.065000 0.105263 200\n", " 11 0.076923 0.009639 0.017131 415\n", " 12 0.066667 0.005181 0.009615 386\n", " 13 0.000000 0.000000 0.000000 301\n", " 14 0.000000 0.000000 0.000000 261\n", " 15 0.000000 0.000000 0.000000 252\n", " 16 0.000000 0.000000 0.000000 252\n", " 17 0.050000 0.003968 0.007353 252\n", " 18 0.000000 0.000000 0.000000 226\n", " 19 0.876037 0.986747 0.928102 18184\n", " 20 0.599057 0.585253 0.592075 651\n", "\n", "avg / total 0.769197 0.857998 0.808970 21380\n", "\n", "Classification report for turbine 18, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.027778 0.019231 0.022727 52\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.095238 0.027778 0.043011 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.941632 0.974887 0.957971 15092\n", " 20 0.980345 0.934099 0.956663 5660\n", "\n", "avg / total 0.924610 0.935594 0.929686 21380\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 18, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.083455 0.220077 0.121019 259\n", " 11 0.000000 0.000000 0.000000 180\n", " 12 0.000000 0.000000 0.000000 121\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.011364 0.009259 0.010204 108\n", " 15 0.009709 0.009259 0.009479 108\n", " 16 0.017544 0.027778 0.021505 108\n", " 17 0.015267 0.018519 0.016736 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.931368 0.898823 0.914806 18344\n", " 20 0.765792 0.431072 0.551628 1828\n", "\n", "avg / total 0.865870 0.811038 0.833825 21380\n", "\n", "Classification report for turbine 18, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.013006 0.089109 0.022699 101\n", " 11 0.000000 0.000000 0.000000 110\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.947423 0.948610 0.948016 19167\n", " 20 0.658466 0.365169 0.469799 1246\n", "\n", "avg / total 0.887793 0.872123 0.877375 21380\n", "\n", "Classification report for turbine 18, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 21\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.945265 0.964623 0.954845 17921\n", " 20 0.959651 0.732381 0.830753 3150\n", "\n", "avg / total 0.933723 0.916464 0.922762 21380\n", "\n", "Classification report for turbine 18, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.986693 0.986165 0.986429 20527\n", " 20 0.833333 0.597890 0.696246 853\n", "\n", "avg / total 0.980575 0.970674 0.974851 21380\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 18, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.982570 0.989531 0.986038 15666\n", " 20 0.981061 0.824991 0.896283 5714\n", "\n", "avg / total 0.982166 0.945557 0.962050 21380\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 18, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.985498 0.996012 0.990727 19309\n", " 20 0.958713 0.863351 0.908537 2071\n", "\n", "avg / total 0.982904 0.983162 0.982766 21380\n", "\n", "Classification report for turbine 18, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.991659 0.991610 0.991634 20023\n", " 20 0.876289 0.876934 0.876611 1357\n", "\n", "avg / total 0.984337 0.984331 0.984334 21380\n", "\n", "Classification report for turbine 18, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.960707 0.994982 0.977544 18135\n", " 20 0.964973 0.772573 0.858121 3245\n", "\n", "avg / total 0.961355 0.961225 0.959418 21380\n", "\n", "Classification report for turbine 18, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.988531 0.995177 0.991843 20527\n", " 20 0.861538 0.722157 0.785714 853\n", "\n", "avg / total 0.983465 0.984284 0.983619 21380\n", "\n", "Classification report for turbine 18, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.984105 0.995915 0.989975 15666\n", " 20 0.988418 0.955898 0.971886 5714\n", "\n", "avg / total 0.985258 0.985220 0.985140 21380\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 18, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.333333 0.069767 0.115385 43\n", " 11 0.017241 0.007937 0.010870 252\n", " 12 0.041667 0.003968 0.007246 252\n", " 13 0.000000 0.000000 0.000000 252\n", " 14 0.000000 0.000000 0.000000 252\n", " 15 0.045455 0.003968 0.007299 252\n", " 16 0.000000 0.000000 0.000000 252\n", " 17 0.027397 0.007937 0.012308 252\n", " 18 0.000000 0.000000 0.000000 252\n", " 19 0.883941 0.977033 0.928158 17329\n", " 20 0.938111 0.867470 0.901408 1992\n", "\n", "avg / total 0.806083 0.873152 0.836956 21380\n", "\n", "Classification report for turbine 18, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.052632 0.153846 0.078431 13\n", " 11 0.015152 0.013889 0.014493 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.018182 0.013889 0.015748 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.019231 0.013889 0.016129 72\n", " 19 0.963383 0.962094 0.962738 19443\n", " 20 0.851478 0.876113 0.863620 1348\n", "\n", "avg / total 0.929996 0.930402 0.930170 21380\n", "\n", "Classification report for turbine 18, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.166667 0.111111 0.133333 18\n", " 11 0.020408 0.009259 0.012739 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.022222 0.009259 0.013072 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.916095 0.980638 0.947269 17302\n", " 20 0.966275 0.770964 0.857640 3196\n", "\n", "avg / total 0.886160 0.909027 0.895035 21380\n", "\n", "Classification report for turbine 18, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 18\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.948074 0.983051 0.965246 19706\n", " 20 0.790251 0.675505 0.728387 792\n", "\n", "avg / total 0.903116 0.931104 0.916652 21380\n", "\n", "Classification report for turbine 18, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 7\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.047619 0.027778 0.035088 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.962754 0.988296 0.975358 15379\n", " 20 0.988182 0.923239 0.954607 5706\n", "\n", "avg / total 0.956337 0.957343 0.956421 21380\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 18, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.985447 0.995960 0.990676 19309\n", " 20 0.958177 0.862868 0.908028 2071\n", "\n", "avg / total 0.982806 0.983068 0.982670 21380\n", "\n", "Classification report for turbine 18, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.991905 0.991360 0.991632 20023\n", " 20 0.873538 0.880619 0.877064 1357\n", "\n", "avg / total 0.984392 0.984331 0.984361 21380\n", "\n", "Classification report for turbine 18, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.961780 0.996305 0.978738 18135\n", " 20 0.974171 0.778737 0.865559 3245\n", "\n", "avg / total 0.963661 0.963283 0.961560 21380\n", "\n", "Classification report for turbine 18, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.988392 0.995518 0.991942 20527\n", " 20 0.869504 0.718640 0.786906 853\n", "\n", "avg / total 0.983648 0.984471 0.983762 21380\n", "\n", "Classification report for turbine 18, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.987084 0.995149 0.991100 15666\n", " 20 0.986395 0.964298 0.975221 5714\n", "\n", "avg / total 0.986900 0.986904 0.986856 21380\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 18, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.984484 0.995650 0.990035 19309\n", " 20 0.954644 0.853694 0.901351 2071\n", "\n", "avg / total 0.981593 0.981899 0.981445 21380\n", "\n", "Classification report for turbine 18, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.992115 0.992858 0.992486 20023\n", " 20 0.893443 0.883567 0.888477 1357\n", "\n", "avg / total 0.985852 0.985921 0.985885 21380\n", "\n", "Classification report for turbine 18, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.956121 0.996085 0.975694 18135\n", " 20 0.971452 0.744530 0.842987 3245\n", "\n", "avg / total 0.958448 0.957905 0.955552 21380\n", "\n", "Classification report for turbine 18, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 15\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.975410 0.995308 0.985259 20246\n", " 20 0.844660 0.732852 0.784794 831\n", "\n", "avg / total 0.956505 0.971001 0.963504 21380\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 18, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 19 0.987010 0.994255 0.990619 15666\n", " 20 0.985863 0.964123 0.974872 5714\n", "\n", "avg / total 0.986703 0.986202 0.986410 21380\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 19, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.986185 0.976799 0.981470 21120\n", " 20 0.763359 0.573066 0.654664 698\n", "\n", "avg / total 0.979056 0.963883 0.971014 21818\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 19, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.222222 0.050000 0.081633 160\n", " 11 0.000000 0.000000 0.000000 198\n", " 12 0.000000 0.000000 0.000000 144\n", " 13 0.000000 0.000000 0.000000 144\n", " 14 0.000000 0.000000 0.000000 144\n", " 15 0.000000 0.000000 0.000000 144\n", " 16 0.000000 0.000000 0.000000 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.931101 0.976728 0.953369 18305\n", " 20 0.742718 0.855147 0.794977 2147\n", "\n", "avg / total 0.855898 0.903978 0.878692 21818\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 19, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 40\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.877248 0.985740 0.928335 15638\n", " 20 0.897429 0.641774 0.748370 5276\n", "\n", "avg / total 0.845780 0.861720 0.846352 21818\n", "\n", "Classification report for turbine 19, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 102\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.957512 0.987601 0.972324 19921\n", " 20 0.850598 0.700574 0.768331 1219\n", "\n", "avg / total 0.921784 0.940875 0.930711 21818\n", "\n", "Classification report for turbine 19, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.166667 0.142857 0.153846 7\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.055556 0.027778 0.037037 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.979437 0.992798 0.986072 20966\n", " 20 0.883562 0.694794 0.777889 557\n", "\n", "avg / total 0.963892 0.971858 0.967535 21818\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 19, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.986912 0.985417 0.986164 21120\n", " 20 0.777164 0.604585 0.680097 698\n", "\n", "avg / total 0.980202 0.973233 0.976372 21818\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 19, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.979484 0.981005 0.980244 19321\n", " 20 0.877875 0.840609 0.858838 2497\n", "\n", "avg / total 0.967855 0.964937 0.966350 21818\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program 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"\n", "avg / total 0.960210 0.963883 0.962027 21818\n", "\n", "Classification report for turbine 19, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.894602 0.714579 0.794521 487\n", " 11 0.000000 0.000000 0.000000 379\n", " 12 0.000000 0.000000 0.000000 360\n", " 13 0.000000 0.000000 0.000000 360\n", " 14 0.000000 0.000000 0.000000 360\n", " 15 0.000000 0.000000 0.000000 360\n", " 16 0.000000 0.000000 0.000000 360\n", " 17 0.000000 0.000000 0.000000 360\n", " 18 0.000000 0.000000 0.000000 360\n", " 19 0.860833 0.993320 0.922344 18115\n", " 20 0.466102 0.694006 0.557668 317\n", "\n", "avg / total 0.741471 0.850765 0.791638 21818\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 19, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 19 0.988030 0.992708 0.990364 21120\n", " 20 0.742475 0.636103 0.685185 698\n", "\n", "avg / total 0.980174 0.981300 0.980600 21818\n", "\n", "Classification report for turbine 19, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 19 0.983861 0.984421 0.984141 19321\n", " 20 0.878922 0.875050 0.876982 2497\n", "\n", "avg / total 0.971851 0.971904 0.971877 21818\n", "\n", "Classification report for turbine 19, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 19 0.942473 0.987342 0.964386 16195\n", " 20 0.957749 0.826427 0.887255 5623\n", "\n", "avg / total 0.946410 0.945870 0.944508 21818\n", "\n", "Classification report for turbine 19, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 19 0.992030 0.995173 0.993599 20511\n", " 20 0.920290 0.874522 0.896822 1307\n", "\n", "avg / total 0.987732 0.987946 0.987802 21818\n", "\n", "Classification report for turbine 19, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 19 0.994930 0.997036 0.995982 21255\n", " 20 0.878378 0.808171 0.841813 563\n", "\n", "avg / total 0.991922 0.992162 0.992003 21818\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 19, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 78\n", " 11 0.000000 0.000000 0.000000 144\n", " 12 0.000000 0.000000 0.000000 128\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.004376 0.018519 0.007080 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.942419 0.946810 0.944609 20173\n", " 20 0.676732 0.588872 0.629752 647\n", "\n", "avg / total 0.891453 0.892978 0.892099 21818\n", "\n", "Classification report for turbine 19, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.005650 0.023256 0.009091 43\n", " 11 0.000000 0.000000 0.000000 144\n", " 12 0.030303 0.006944 0.011299 144\n", " 13 0.000000 0.000000 0.000000 144\n", " 14 0.000000 0.000000 0.000000 144\n", " 15 0.000000 0.000000 0.000000 144\n", " 16 0.000000 0.000000 0.000000 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.938674 0.961892 0.950141 18395\n", " 20 0.780145 0.871185 0.823155 2228\n", "\n", "avg / total 0.871284 0.900037 0.885226 21818\n", "\n", "Classification report for turbine 19, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 12\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 85\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.904016 0.938660 0.921012 15683\n", " 20 0.925976 0.756174 0.832505 5426\n", "\n", "avg / total 0.880100 0.862774 0.869072 21818\n", "\n", "Classification report for turbine 19, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.636364 0.033816 0.064220 414\n", " 11 0.000000 0.000000 0.000000 252\n", " 12 0.000000 0.000000 0.000000 252\n", " 13 0.014286 0.003968 0.006211 252\n", " 14 0.000000 0.000000 0.000000 230\n", " 15 0.000000 0.000000 0.000000 216\n", " 16 0.000000 0.000000 0.000000 216\n", " 17 0.000000 0.000000 0.000000 216\n", " 18 0.000000 0.000000 0.000000 215\n", " 19 0.896941 0.981596 0.937361 18637\n", " 20 0.621570 0.715686 0.665316 918\n", "\n", "avg / total 0.804562 0.869282 0.829980 21818\n", "\n", "Classification report for turbine 19, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 4\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.980291 0.953460 0.966689 20971\n", " 20 0.867841 0.709910 0.780971 555\n", "\n", "avg / total 0.964311 0.934504 0.949027 21818\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 19, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.054795 0.016327 0.025157 245\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.973462 0.953262 0.963256 20818\n", " 20 0.287986 0.349036 0.315586 467\n", "\n", "avg / total 0.935624 0.917224 0.926144 21818\n", "\n", "Classification report for turbine 19, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.058824 0.032967 0.042254 364\n", " 11 0.149171 0.187500 0.166154 144\n", " 12 0.000000 0.000000 0.000000 144\n", " 13 0.000000 0.000000 0.000000 144\n", " 14 0.000000 0.000000 0.000000 144\n", " 15 0.000000 0.000000 0.000000 144\n", " 16 0.000000 0.000000 0.000000 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.924850 0.963877 0.943961 18271\n", " 20 0.778605 0.824225 0.800765 2031\n", "\n", "avg / total 0.848940 0.885691 0.866842 21818\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 19, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.697674 0.206186 0.318302 873\n", " 11 0.002915 0.002778 0.002845 360\n", " 12 0.000000 0.000000 0.000000 326\n", " 13 0.000000 0.000000 0.000000 324\n", " 14 0.000000 0.000000 0.000000 318\n", " 15 0.104167 0.017361 0.029762 288\n", " 16 0.100000 0.006944 0.012987 288\n", " 17 0.000000 0.000000 0.000000 286\n", " 18 0.000000 0.000000 0.000000 247\n", " 19 0.771391 0.945556 0.849640 13739\n", " 20 0.865428 0.732229 0.793276 4769\n", "\n", "avg / total 0.705577 0.764094 0.721769 21818\n", "\n", "Classification report for turbine 19, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.987391 0.969724 0.978477 20511\n", " 20 0.936590 0.689365 0.794182 1307\n", "\n", "avg / total 0.984348 0.952929 0.967437 21818\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 19, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 5\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.980453 0.968486 0.974433 20975\n", " 20 0.844017 0.718182 0.776031 550\n", "\n", "avg / total 0.963847 0.949170 0.956345 21818\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 19, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.988041 0.993608 0.990817 21120\n", " 20 0.766839 0.636103 0.695380 698\n", "\n", "avg / total 0.980964 0.982171 0.981365 21818\n", "\n", "Classification report for turbine 19, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 128\n", " 11 0.000000 0.000000 0.000000 77\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.948905 0.983589 0.965936 18768\n", " 20 0.830795 0.838958 0.834857 2341\n", "\n", "avg / total 0.905397 0.936108 0.920482 21818\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 19, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 126\n", " 11 0.000000 0.000000 0.000000 190\n", " 12 0.000000 0.000000 0.000000 144\n", " 13 0.000000 0.000000 0.000000 144\n", " 14 0.000000 0.000000 0.000000 144\n", " 15 0.000000 0.000000 0.000000 144\n", " 16 0.000000 0.000000 0.000000 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.877051 0.960745 0.916993 15132\n", " 20 0.917387 0.811824 0.861383 5362\n", "\n", "avg / total 0.833741 0.865845 0.847679 21818\n", "\n", "Classification report for turbine 19, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.987179 0.983521 0.985347 20511\n", " 20 0.943609 0.768171 0.846900 1307\n", "\n", "avg / total 0.984569 0.970621 0.977053 21818\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 19, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.993647 0.993460 0.993554 21255\n", " 20 0.903226 0.746004 0.817121 563\n", "\n", "avg / total 0.991314 0.987075 0.989001 21818\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 19, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 52\n", " 11 0.026316 0.010417 0.014925 288\n", " 12 0.050000 0.003472 0.006494 288\n", " 13 0.000000 0.000000 0.000000 288\n", " 14 0.000000 0.000000 0.000000 288\n", " 15 0.058824 0.027778 0.037736 288\n", " 16 0.000000 0.000000 0.000000 257\n", " 17 0.000000 0.000000 0.000000 252\n", " 18 0.000000 0.000000 0.000000 252\n", " 19 0.886385 0.982159 0.931818 18945\n", " 20 0.720841 0.608065 0.659668 620\n", "\n", "avg / total 0.791934 0.870657 0.828642 21818\n", "\n", "Classification report for turbine 19, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 16\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.022222 0.009259 0.013072 108\n", " 15 0.021277 0.009259 0.012903 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.937170 0.961018 0.948944 18470\n", " 20 0.866075 0.830632 0.847983 2468\n", "\n", "avg / total 0.891544 0.907599 0.899378 21818\n", "\n", "Classification report for turbine 19, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.111111 0.136364 0.122449 22\n", " 11 0.000000 0.000000 0.000000 124\n", " 12 0.060606 0.018519 0.028369 108\n", " 13 0.018519 0.009259 0.012346 108\n", " 14 0.022222 0.018519 0.020202 108\n", " 15 0.011494 0.009259 0.010256 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.020833 0.009259 0.012821 108\n", " 19 0.886369 0.963229 0.923202 15338\n", " 20 0.950851 0.801183 0.869624 5578\n", "\n", "avg / total 0.866984 0.882437 0.871876 21818\n", "\n", "Classification report for turbine 19, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.200000 0.033333 0.057143 30\n", " 11 0.000000 0.000000 0.000000 180\n", " 12 0.000000 0.000000 0.000000 180\n", " 13 0.033333 0.005556 0.009524 180\n", " 14 0.000000 0.000000 0.000000 180\n", " 15 0.057143 0.011111 0.018605 180\n", " 16 0.000000 0.000000 0.000000 180\n", " 17 0.000000 0.000000 0.000000 180\n", " 18 0.019608 0.005556 0.008658 180\n", " 19 0.923277 0.982850 0.952133 19125\n", " 20 0.850885 0.825838 0.838174 1223\n", "\n", "avg / total 0.858196 0.908058 0.881976 21818\n", "\n", "Classification report for turbine 19, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 24\n", " 11 0.000000 0.000000 0.000000 144\n", " 12 0.000000 0.000000 0.000000 144\n", " 13 0.000000 0.000000 0.000000 144\n", " 14 0.000000 0.000000 0.000000 144\n", " 15 0.103448 0.020833 0.034682 144\n", " 16 0.096774 0.020833 0.034286 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.940917 0.984838 0.962376 20116\n", " 20 0.816116 0.750951 0.782178 526\n", "\n", "avg / total 0.888514 0.926391 0.906615 21818\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 19, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.988677 0.992235 0.990453 21120\n", " 20 0.736334 0.656160 0.693939 698\n", "\n", "avg / total 0.980604 0.981483 0.980967 21818\n", "\n", "Classification report for turbine 19, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.977288 0.984369 0.980816 19321\n", " 20 0.871871 0.822988 0.846724 2497\n", "\n", "avg / total 0.965223 0.965900 0.965470 21818\n", "\n", "Classification report for turbine 19, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.948491 0.988083 0.967882 16195\n", " 20 0.960986 0.845456 0.899527 5623\n", "\n", "avg / total 0.951712 0.951325 0.950266 21818\n", "\n", "Classification report for turbine 19, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.992365 0.994832 0.993597 20511\n", " 20 0.915605 0.879878 0.897386 1307\n", "\n", "avg / total 0.987766 0.987946 0.987833 21818\n", "\n", "Classification report for turbine 19, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.995023 0.996989 0.996005 21255\n", " 20 0.877159 0.811723 0.843173 563\n", "\n", "avg / total 0.991981 0.992208 0.992061 21818\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 19, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.988460 0.993655 0.991051 21120\n", " 20 0.771721 0.648997 0.705058 698\n", "\n", "avg / total 0.981526 0.982629 0.981902 21818\n", "\n", "Classification report for turbine 19, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.979180 0.985819 0.982488 19321\n", " 20 0.884193 0.837805 0.860374 2497\n", "\n", "avg / total 0.968309 0.968879 0.968512 21818\n", "\n", "Classification report for turbine 19, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.955799 0.990738 0.972955 16195\n", " 20 0.970185 0.868042 0.916276 5623\n", "\n", "avg / total 0.959507 0.959116 0.958347 21818\n", "\n", "Classification report for turbine 19, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 15\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.980500 0.995261 0.987825 20259\n", " 20 0.885167 0.883758 0.884462 1256\n", "\n", "avg / total 0.961395 0.975021 0.968157 21818\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 19, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 6\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.980902 0.997043 0.988906 20966\n", " 20 0.906445 0.781362 0.839269 558\n", "\n", "avg / total 0.965780 0.978091 0.971754 21818\n", "\n", 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0.937439 0.946401 0.941531 21754\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 20, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 1.000000 0.016949 0.033333 59\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 102\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.939539 0.986451 0.962424 15942\n", " 20 0.928414 0.925445 0.926927 5003\n", "\n", "avg / total 0.904752 0.935782 0.918559 21754\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 20, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 8\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.926368 0.991020 0.957604 19487\n", " 20 0.883292 0.364789 0.516338 1971\n", "\n", "avg / total 0.909861 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0.000000 0.000000 144\n", " 15 0.000000 0.000000 0.000000 144\n", " 16 0.018868 0.006944 0.010152 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.920977 0.981440 0.950248 19558\n", " 20 0.749004 0.410033 0.529951 917\n", "\n", "avg / total 0.863208 0.903282 0.880273 21754\n", "\n", "Classification report for turbine 20, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.086957 0.115942 0.099379 69\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.076923 0.027778 0.040816 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.947925 0.968624 0.958163 16669\n", " 20 0.941014 0.867174 0.902587 4728\n", "\n", "avg / total 0.931270 0.931093 0.930742 21754\n", "\n", "Classification report for turbine 20, turbine category 3.0\n", 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warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 20, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 19 0.980923 0.994248 0.987541 20687\n", " 20 0.848601 0.625117 0.719914 1067\n", "\n", "avg / total 0.974433 0.976142 0.974414 21754\n", "\n", "Classification report for turbine 20, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 19 0.968251 0.984998 0.976553 16998\n", " 20 0.942851 0.884567 0.912779 4756\n", "\n", "avg / total 0.962698 0.963041 0.962610 21754\n", "\n", "Classification report for turbine 20, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 19 0.979526 0.987924 0.983707 16562\n", " 20 0.960396 0.934129 0.947081 5192\n", "\n", "avg / total 0.974960 0.975085 0.974966 21754\n", "\n", "Classification report for turbine 20, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 19 0.953098 0.995601 0.973886 19778\n", " 20 0.920475 0.509615 0.656026 1976\n", "\n", "avg / total 0.950135 0.951457 0.945014 21754\n", "\n", "Classification report for turbine 20, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 19 0.988541 0.988666 0.988603 15793\n", " 20 0.969961 0.969636 0.969799 5961\n", "\n", "avg / total 0.983450 0.983451 0.983450 21754\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 20, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.111111 0.010204 0.018692 98\n", " 11 0.000000 0.000000 0.000000 89\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 70\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.950034 0.983339 0.966399 20167\n", " 20 0.793388 0.494845 0.609524 970\n", "\n", "avg / total 0.916604 0.933713 0.923161 21754\n", "\n", "Classification report for turbine 20, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.032258 0.003322 0.006024 602\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.055556 0.027778 0.037037 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.954243 0.974696 0.964361 16796\n", " 20 0.776883 0.806293 0.791315 4068\n", "\n", "avg / total 0.883022 0.903466 0.892776 21754\n", "\n", "Classification report for turbine 20, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.011278 0.500000 0.022059 12\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.058824 0.009901 0.016949 101\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.939455 0.959343 0.949295 16061\n", " 20 0.918075 0.870235 0.893515 4932\n", "\n", "avg / total 0.902023 0.905902 0.903531 21754\n", "\n", "Classification report for turbine 20, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 22\n", " 11 0.000000 0.000000 0.000000 123\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 83\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 79\n", " 19 0.909047 0.988701 0.947202 19116\n", " 20 0.807082 0.348078 0.486387 1899\n", "\n", "avg / total 0.869265 0.899191 0.874799 21754\n", "\n", "Classification report for turbine 20, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 12\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.761420 0.986229 0.859366 15177\n", " 20 0.939846 0.320646 0.478159 5701\n", "\n", "avg / total 0.777518 0.772088 0.724859 21754\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 20, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 19 0.977722 0.994973 0.986272 20687\n", " 20 0.851852 0.560450 0.676088 1067\n", "\n", "avg / total 0.971548 0.973660 0.971058 21754\n", "\n", "Classification report for turbine 20, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 19 0.969587 0.986528 0.977984 16998\n", " 20 0.948643 0.889403 0.918068 4756\n", "\n", "avg / total 0.965008 0.965294 0.964885 21754\n", "\n", "Classification report for turbine 20, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 316\n", " 11 0.000000 0.000000 0.000000 255\n", " 12 0.000000 0.000000 0.000000 214\n", " 13 0.000000 0.000000 0.000000 162\n", " 14 0.000000 0.000000 0.000000 144\n", " 15 0.000000 0.000000 0.000000 134\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 99\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.924654 0.987327 0.954963 15624\n", " 20 0.853086 0.935149 0.892235 4626\n", "\n", "avg / total 0.845507 0.907971 0.875601 21754\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 20, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 89\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 45\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.926416 0.992710 0.958418 19480\n", " 20 0.745124 0.309395 0.437238 1852\n", "\n", "avg / total 0.893010 0.915280 0.895456 21754\n", "\n", "Classification report for turbine 20, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 81\n", " 11 0.000000 0.000000 0.000000 180\n", " 12 0.000000 0.000000 0.000000 180\n", " 13 0.000000 0.000000 0.000000 178\n", " 14 0.000000 0.000000 0.000000 144\n", " 15 0.000000 0.000000 0.000000 144\n", " 16 0.000000 0.000000 0.000000 144\n", " 17 0.000000 0.000000 0.000000 144\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.847050 0.977131 0.907452 14736\n", " 20 0.904957 0.739391 0.813839 5679\n", "\n", "avg / total 0.810029 0.854923 0.827159 21754\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 20, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 33\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.006711 0.027778 0.010811 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.958598 0.969515 0.964026 20371\n", " 20 0.807757 0.451036 0.578852 1062\n", "\n", "avg / total 0.937101 0.929944 0.931015 21754\n", "\n", "Classification report for turbine 20, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.071429 0.055046 0.062176 109\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 65\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.962661 0.974966 0.968775 16977\n", " 20 0.841690 0.854584 0.848088 4243\n", "\n", "avg / total 0.915794 0.927829 0.921766 21754\n", "\n", "Classification report for turbine 20, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.185000 0.066249 0.097561 1117\n", " 11 0.000000 0.000000 0.000000 258\n", " 12 0.000000 0.000000 0.000000 216\n", " 13 0.000000 0.000000 0.000000 202\n", " 14 0.000000 0.000000 0.000000 180\n", " 15 0.000000 0.000000 0.000000 180\n", " 16 0.000000 0.000000 0.000000 180\n", " 17 0.000000 0.000000 0.000000 173\n", " 18 0.000000 0.000000 0.000000 144\n", " 19 0.888800 0.954848 0.920641 15193\n", " 20 0.718303 0.757607 0.737432 3911\n", "\n", "avg / total 0.759376 0.806472 0.780563 21754\n", "\n", "Classification report for turbine 20, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.938258 0.985792 0.961438 19778\n", " 20 0.879617 0.325405 0.475065 1976\n", "\n", "avg / total 0.932931 0.925807 0.917259 21754\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: 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108\n", " 19 0.942760 0.905712 0.923865 15930\n", " 20 0.770732 0.217282 0.338995 4363\n", "\n", "avg / total 0.848208 0.729291 0.750109 21754\n", "\n", "Classification report for turbine 20, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.940485 0.982759 0.961157 19778\n", " 20 0.843478 0.196356 0.318555 1976\n", "\n", "avg / total 0.931673 0.911327 0.902787 21754\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 20, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.045620 0.284091 0.078616 88\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.854783 0.980405 0.913294 15412\n", " 20 0.921185 0.547552 0.686844 5678\n", "\n", "avg / total 0.846209 0.838650 0.826630 21754\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 20, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.978615 0.995456 0.986964 20687\n", " 20 0.867792 0.578257 0.694038 1067\n", "\n", "avg / total 0.973180 0.974993 0.972596 21754\n", "\n", "Classification report for turbine 20, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 19 0.969539 0.986822 0.978104 16998\n", " 20 0.949697 0.889193 0.918449 4756\n", "\n", "avg / total 0.965201 0.965478 0.965062 21754\n", "\n", "Classification report for turbine 20, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 6\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.965115 0.985384 0.975144 16284\n", " 20 0.950858 0.942040 0.946429 5176\n", "\n", "avg / total 0.948679 0.961754 0.955133 21754\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program 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0.966960 0.953677 16011\n", " 20 0.954295 0.907451 0.930283 5154\n", "\n", "avg / total 0.918521 0.926726 0.922350 21754\n", "\n", "Classification report for turbine 20, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 16\n", " 11 0.034483 0.009259 0.014599 108\n", " 12 0.020833 0.009259 0.012821 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.904405 0.983955 0.942504 19009\n", " 20 0.862651 0.383914 0.531354 1865\n", "\n", "avg / total 0.864515 0.892801 0.869266 21754\n", "\n", "Classification report for turbine 20, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 19\n", " 11 0.050000 0.009259 0.015625 108\n", " 12 0.033333 0.009259 0.014493 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 108\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 108\n", " 19 0.861416 0.980750 0.917218 15065\n", " 20 0.932688 0.713572 0.808548 5806\n", "\n", "avg / total 0.845886 0.869725 0.851134 21754\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 20, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.974704 0.994634 0.984568 20687\n", " 20 0.827640 0.499531 0.623027 1067\n", "\n", "avg / total 0.967491 0.970350 0.966835 21754\n", "\n", "Classification report for turbine 20, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.961896 0.986116 0.973855 16998\n", " 20 0.945471 0.860387 0.900925 4756\n", "\n", "avg / total 0.958305 0.958628 0.957911 21754\n", "\n", "Classification report for turbine 20, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.978727 0.988951 0.983812 16562\n", " 20 0.963539 0.931433 0.947214 5192\n", "\n", "avg / total 0.975102 0.975223 0.975077 21754\n", "\n", "Classification report for turbine 20, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.943497 0.995399 0.968753 19778\n", " 20 0.897523 0.403340 0.556564 1976\n", "\n", "avg / total 0.939321 0.941620 0.931312 21754\n", "\n", "Classification report for turbine 20, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.959558 0.994555 0.976743 15793\n", " 20 0.984030 0.888945 0.934074 5961\n", "\n", "avg / total 0.966263 0.965616 0.965051 21754\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 20, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.976583 0.993861 0.985146 20687\n", " 20 0.818830 0.537957 0.649321 1067\n", "\n", "avg / total 0.968845 0.971499 0.968674 21754\n", "\n", "Classification report for turbine 20, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.959908 0.987410 0.973465 16998\n", " 20 0.949871 0.852607 0.898615 4756\n", "\n", "avg / total 0.957714 0.957939 0.957101 21754\n", "\n", "Classification report for turbine 20, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.981339 0.987502 0.984411 16562\n", " 20 0.959316 0.940100 0.949611 5192\n", "\n", "avg / total 0.976083 0.976188 0.976105 21754\n", "\n", "Classification report for turbine 20, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 17\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.930613 0.995129 0.961790 19502\n", " 20 0.864444 0.399589 0.546540 1947\n", "\n", "avg / total 0.911643 0.927875 0.911140 21754\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 20, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.897699 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" 18 0.000000 0.000000 0.000000 26\n", " 19 0.977014 0.987098 0.982030 15114\n", " 20 0.751530 0.826380 0.787179 743\n", "\n", "avg / total 0.952631 0.965562 0.958990 16087\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 21, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 19 0.991283 0.987218 0.989247 14630\n", " 20 0.879630 0.912835 0.895925 1457\n", "\n", "avg / total 0.981171 0.980481 0.980794 16087\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 21, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 19 0.958059 0.995070 0.976214 13590\n", " 20 0.969959 0.762915 0.854069 2497\n", "\n", "avg / total 0.959906 0.959035 0.957255 16087\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for 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"------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 21, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 19 0.992357 0.990546 0.991451 15337\n", " 20 0.813625 0.844000 0.828534 750\n", "\n", "avg / total 0.984025 0.983714 0.983855 16087\n", "\n", "Classification report for turbine 21, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 19 0.992236 0.987081 0.989652 14630\n", " 20 0.876712 0.922443 0.898997 1457\n", "\n", "avg / total 0.981773 0.981227 0.981441 16087\n", "\n", "Classification report for turbine 21, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 108\n", " 11 0.000000 0.000000 0.000000 30\n", " 12 0.000000 0.000000 0.000000 30\n", " 13 0.000000 0.000000 0.000000 26\n", " 14 0.000000 0.000000 0.000000 20\n", " 15 0.000000 0.000000 0.000000 27\n", " 16 0.000000 0.000000 0.000000 27\n", " 17 0.000000 0.000000 0.000000 27\n", " 18 0.000000 0.000000 0.000000 26\n", " 19 0.952316 0.995957 0.973648 13355\n", " 20 0.936792 0.823725 0.876628 2411\n", "\n", "avg / total 0.930987 0.950270 0.939679 16087\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 21, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.994537 0.992577 0.993556 15223\n", " 20 0.926278 0.901620 0.913783 864\n", "\n", "avg / total 0.990871 0.987692 0.989272 16087\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 21, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.994270 0.996195 0.995231 14979\n", " 20 0.955056 0.920578 0.937500 1108\n", "\n", "avg / total 0.991569 0.990987 0.991255 16087\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 21, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.993749 0.984743 0.989225 15337\n", " 20 0.736783 0.873333 0.799268 750\n", "\n", "avg / total 0.981769 0.979549 0.980369 16087\n", "\n", "Classification report for turbine 21, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.992254 0.989405 0.990828 14630\n", " 20 0.896598 0.922443 0.909337 1457\n", "\n", "avg / total 0.983590 0.983341 0.983447 16087\n", "\n", "Classification report for turbine 21, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.968001 0.994996 0.981313 13590\n", " 20 0.967894 0.820985 0.888407 2497\n", "\n", "avg / total 0.967984 0.967987 0.966892 16087\n", "\n", "Classification report for turbine 21, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.995861 0.995730 0.995796 15223\n", " 20 0.924942 0.927083 0.926012 864\n", "\n", "avg / total 0.992052 0.992043 0.992048 16087\n", "\n", "Classification report for turbine 21, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.994208 0.996996 0.995600 14979\n", " 20 0.957786 0.921480 0.939282 1108\n", "\n", "avg / total 0.991700 0.991795 0.991721 16087\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 21, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.989455 0.978875 0.984136 15337\n", " 20 0.740088 0.672000 0.704403 750\n", "\n", "avg / total 0.977829 0.964568 0.971095 16087\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 21, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 24\n", " 11 0.000000 0.000000 0.000000 30\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 28\n", " 14 0.000000 0.000000 0.000000 28\n", " 15 0.000000 0.000000 0.000000 29\n", " 16 0.000000 0.000000 0.000000 29\n", " 17 0.000000 0.000000 0.000000 27\n", " 18 0.000000 0.000000 0.000000 28\n", " 19 0.986075 0.988098 0.987086 14620\n", " 20 0.722590 0.812914 0.765095 1208\n", "\n", "avg / total 0.950414 0.959035 0.954524 16087\n", "\n", "Classification report for turbine 21, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.078431 0.363636 0.129032 11\n", " 11 0.000000 0.000000 0.000000 62\n", " 12 0.000000 0.000000 0.000000 52\n", " 13 0.000000 0.000000 0.000000 55\n", " 14 0.000000 0.000000 0.000000 49\n", " 15 0.000000 0.000000 0.000000 53\n", " 16 0.000000 0.000000 0.000000 54\n", " 17 0.000000 0.000000 0.000000 56\n", " 18 0.000000 0.000000 0.000000 51\n", " 19 0.928571 0.975469 0.951443 13167\n", " 20 0.955929 0.735567 0.831394 2477\n", "\n", "avg / total 0.907267 0.911916 0.906846 16087\n", "\n", "Classification report for turbine 21, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 57\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.000000 0.000000 0.000000 108\n", " 13 0.000000 0.000000 0.000000 108\n", " 14 0.000000 0.000000 0.000000 106\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.000000 0.000000 0.000000 105\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 106\n", " 19 0.937389 0.987270 0.961683 14376\n", " 20 0.853315 0.759097 0.803453 797\n", "\n", "avg / total 0.879965 0.919873 0.899205 16087\n", "\n", "Classification report for turbine 21, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.013889 0.200000 0.025974 5\n", " 11 0.000000 0.000000 0.000000 20\n", " 12 0.000000 0.000000 0.000000 23\n", " 13 0.000000 0.000000 0.000000 33\n", " 14 0.000000 0.000000 0.000000 35\n", " 15 0.000000 0.000000 0.000000 34\n", " 16 0.000000 0.000000 0.000000 33\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.987996 0.977259 0.982598 14907\n", " 20 0.784008 0.816216 0.799788 925\n", "\n", "avg / total 0.960610 0.952570 0.956519 16087\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 21, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 19 0.989976 0.985199 0.987582 15337\n", " 20 0.784676 0.792000 0.788321 750\n", "\n", "avg / total 0.980404 0.976192 0.978292 16087\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 21, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 19 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"\n", "avg / total 0.971238 0.971157 0.970242 16087\n", "\n", "Classification report for turbine 21, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 19 0.995537 0.996321 0.995929 15223\n", " 20 0.934272 0.921296 0.927739 864\n", "\n", "avg / total 0.992246 0.992292 0.992266 16087\n", "\n", "Classification report for turbine 21, turbine category 7.0\n", " precision recall f1-score support\n", "\n", " 19 0.994542 0.997463 0.996000 14979\n", " 20 0.964286 0.925993 0.944751 1108\n", "\n", "avg / total 0.992458 0.992541 0.992470 16087\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 21, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.991288 0.971833 0.981464 15337\n", " 20 0.725749 0.808000 0.764669 750\n", "\n", "avg / total 0.978908 0.964195 0.971356 16087\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 21, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 23\n", " 11 0.000000 0.000000 0.000000 102\n", " 12 0.000000 0.000000 0.000000 96\n", " 13 0.000000 0.000000 0.000000 89\n", " 14 0.000000 0.000000 0.000000 95\n", " 15 0.400000 0.023529 0.044444 85\n", " 16 0.000000 0.000000 0.000000 86\n", " 17 0.000000 0.000000 0.000000 83\n", " 18 0.000000 0.000000 0.000000 81\n", " 19 0.966445 0.989275 0.977727 14266\n", " 20 0.676164 0.900093 0.772222 1081\n", "\n", "avg / total 0.904596 0.937900 0.919177 16087\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 21, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 16\n", " 11 0.000000 0.000000 0.000000 27\n", " 12 0.000000 0.000000 0.000000 28\n", " 13 0.000000 0.000000 0.000000 31\n", " 14 0.000000 0.000000 0.000000 28\n", " 15 0.000000 0.000000 0.000000 28\n", " 16 0.000000 0.000000 0.000000 29\n", " 17 0.000000 0.000000 0.000000 29\n", " 18 0.000000 0.000000 0.000000 22\n", " 19 0.945554 0.990877 0.967685 13373\n", " 20 0.964620 0.748788 0.843111 2476\n", "\n", "avg / total 0.934500 0.938957 0.934195 16087\n", "\n", "Classification report for turbine 21, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.062500 0.026087 0.036810 115\n", " 11 0.000000 0.000000 0.000000 35\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 34\n", " 14 0.000000 0.000000 0.000000 35\n", " 15 0.000000 0.000000 0.000000 34\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.975629 0.991831 0.983663 14934\n", " 20 0.811054 0.834656 0.822686 756\n", "\n", "avg / total 0.944265 0.960154 0.952086 16087\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 21, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.015707 0.016949 0.016304 177\n", " 11 0.000000 0.000000 0.000000 201\n", " 12 0.000000 0.000000 0.000000 176\n", " 13 0.000000 0.000000 0.000000 163\n", " 14 0.000000 0.000000 0.000000 140\n", " 15 0.000000 0.000000 0.000000 144\n", " 16 0.000000 0.000000 0.000000 143\n", " 17 0.000000 0.000000 0.000000 140\n", " 18 0.500000 0.007407 0.014599 135\n", " 19 0.912278 0.983499 0.946551 13757\n", " 20 0.792490 0.880351 0.834113 911\n", "\n", "avg / total 0.829393 0.891154 0.856992 16087\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 21, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 19 0.993046 0.986960 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0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.979578 0.996526 0.987980 14970\n", " 20 0.787879 0.927298 0.851922 729\n", "\n", "avg / total 0.947265 0.969354 0.957985 16087\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 21, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.993545 0.996662 0.995101 14979\n", " 20 0.960539 0.900722 0.929669 1108\n", "\n", "avg / total 0.991271 0.990054 0.990594 16087\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 21, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.410995 0.918129 0.567812 171\n", " 11 0.000000 0.000000 0.000000 88\n", " 12 0.000000 0.000000 0.000000 78\n", " 13 0.009217 0.024390 0.013378 82\n", " 14 0.004854 0.013514 0.007143 74\n", " 15 0.052083 0.063291 0.057143 79\n", " 16 0.006250 0.013158 0.008475 76\n", " 17 0.000000 0.000000 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0.000000 0.000000 0.000000 59\n", " 13 0.000000 0.000000 0.000000 57\n", " 14 0.000000 0.000000 0.000000 51\n", " 15 0.000000 0.000000 0.000000 61\n", " 16 0.000000 0.000000 0.000000 56\n", " 17 0.000000 0.000000 0.000000 55\n", " 18 0.027778 0.017544 0.021505 57\n", " 19 0.934771 0.955162 0.944857 13203\n", " 20 0.933471 0.741196 0.826295 2442\n", "\n", "avg / total 0.908989 0.896500 0.900975 16087\n", "\n", "Classification report for turbine 21, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.169811 0.103448 0.128571 174\n", " 11 0.233333 0.059322 0.094595 118\n", " 12 0.000000 0.000000 0.000000 52\n", " 13 0.000000 0.000000 0.000000 51\n", " 14 0.000000 0.000000 0.000000 28\n", " 15 0.000000 0.000000 0.000000 9\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.980155 0.984599 0.982372 14999\n", " 20 0.691790 0.783537 0.734811 656\n", "\n", "avg / total 0.945623 0.951514 0.947981 16087\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 21, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 8\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.044444 0.027778 0.034188 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 71\n", " 17 0.000000 0.000000 0.000000 71\n", " 18 0.000000 0.000000 0.000000 71\n", " 19 0.955745 0.979949 0.967696 14413\n", " 20 0.922258 0.792315 0.852362 1093\n", "\n", "avg / total 0.919151 0.931933 0.925063 16087\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 21, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 19 0.993312 0.987742 0.990519 15337\n", " 20 0.775120 0.864000 0.817150 750\n", "\n", "avg / total 0.983139 0.981973 0.982436 16087\n", "\n", "Classification report for turbine 21, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 546\n", " 11 0.000000 0.000000 0.000000 146\n", " 12 0.000000 0.000000 0.000000 147\n", " 13 0.000000 0.000000 0.000000 113\n", " 14 0.000000 0.000000 0.000000 112\n", " 15 0.000000 0.000000 0.000000 103\n", " 16 0.000000 0.000000 0.000000 107\n", " 17 0.000000 0.000000 0.000000 102\n", " 18 0.000000 0.000000 0.000000 103\n", " 19 0.927275 0.991827 0.958466 13704\n", " 20 0.547236 0.865044 0.670381 904\n", "\n", "avg / total 0.820668 0.893517 0.854158 16087\n", "\n" ] }, { "name": "stderr", "output_type": "stream", 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"C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 21, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 45\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.975435 0.991764 0.983531 14934\n", " 20 0.863824 0.765854 0.811894 820\n", "\n", "avg / total 0.949554 0.959719 0.954424 16087\n", "\n", "Classification report for turbine 21, turbine category 11.0\n", " precision recall 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0.000000 0.000000 0.000000 54\n", " 18 0.000000 0.000000 0.000000 55\n", " 19 0.959527 0.981056 0.970172 14886\n", " 20 0.626322 0.789630 0.698558 675\n", "\n", "avg / total 0.914172 0.940946 0.927053 16087\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 21, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.142857 0.324324 0.198347 37\n", " 11 0.000000 0.000000 0.000000 77\n", " 12 0.000000 0.000000 0.000000 63\n", " 13 0.000000 0.000000 0.000000 50\n", " 14 0.000000 0.000000 0.000000 56\n", " 15 0.000000 0.000000 0.000000 48\n", " 16 0.000000 0.000000 0.000000 58\n", " 17 0.000000 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Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 21, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.993878 0.991854 0.992865 15223\n", " 20 0.924757 0.881944 0.902844 864\n", "\n", "avg / total 0.990166 0.985951 0.988030 16087\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 21, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 23\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.973411 0.994350 0.983769 14690\n", " 20 0.940777 0.892265 0.915879 1086\n", "\n", "avg / total 0.952389 0.968235 0.960167 16087\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 21, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.052632 0.058824 0.055556 17\n", " 11 0.004098 0.009901 0.005797 101\n", " 12 0.000000 0.000000 0.000000 103\n", " 13 0.000000 0.000000 0.000000 103\n", " 14 0.000000 0.000000 0.000000 116\n", " 15 0.000000 0.000000 0.000000 105\n", " 16 0.000000 0.000000 0.000000 106\n", " 17 0.097902 0.128440 0.111111 109\n", " 18 0.000000 0.000000 0.000000 112\n", " 19 0.937239 0.913643 0.925291 14498\n", " 20 0.707989 0.716876 0.712405 717\n", "\n", "avg / total 0.876963 0.856344 0.866495 16087\n", "\n", "Classification report for turbine 21, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.200000 0.125000 0.153846 8\n", " 11 0.000000 0.000000 0.000000 54\n", " 12 0.000000 0.000000 0.000000 46\n", " 13 0.000000 0.000000 0.000000 46\n", " 14 0.000000 0.000000 0.000000 57\n", " 15 0.000000 0.000000 0.000000 55\n", " 16 0.000000 0.000000 0.000000 47\n", " 17 0.000000 0.000000 0.000000 51\n", " 18 0.045455 0.014925 0.022472 67\n", " 19 0.961409 0.966545 0.963970 14228\n", " 20 0.878596 0.876751 0.877673 1428\n", "\n", "avg / total 0.928589 0.932803 0.930653 16087\n", "\n", "Classification report for turbine 21, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.027397 0.210526 0.048485 19\n", " 11 0.000000 0.000000 0.000000 101\n", " 12 0.015152 0.008696 0.011050 115\n", " 13 0.000000 0.000000 0.000000 110\n", " 14 0.000000 0.000000 0.000000 116\n", " 15 0.000000 0.000000 0.000000 111\n", " 16 0.000000 0.000000 0.000000 106\n", " 17 0.028571 0.009434 0.014184 106\n", " 18 0.000000 0.000000 0.000000 87\n", " 19 0.890758 0.959520 0.923861 12747\n", " 20 0.951486 0.635480 0.762020 2469\n", "\n", "avg / total 0.852179 0.858208 0.849231 16087\n", "\n", "Classification report for turbine 21, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 1.000000 0.045455 0.086957 22\n", " 11 0.000000 0.000000 0.000000 115\n", " 12 0.000000 0.000000 0.000000 118\n", " 13 0.025641 0.008403 0.012658 119\n", " 14 0.000000 0.000000 0.000000 107\n", " 15 0.000000 0.000000 0.000000 111\n", " 16 0.000000 0.000000 0.000000 108\n", " 17 0.000000 0.000000 0.000000 116\n", " 18 0.058824 0.008403 0.014706 119\n", " 19 0.936266 0.974632 0.955064 14349\n", " 20 0.864532 0.874222 0.869350 803\n", "\n", "avg / total 0.880260 0.913160 0.895597 16087\n", "\n", "Classification report for turbine 21, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.250000 0.142857 0.181818 7\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 35\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.186813 0.944444 0.311927 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.978948 0.977683 0.978315 14697\n", " 20 0.952607 0.916971 0.934449 1096\n", "\n", "avg / total 0.959789 0.957854 0.958224 16087\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 21, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.990480 0.990415 0.990448 15337\n", " 20 0.804261 0.805333 0.804797 750\n", "\n", "avg / total 0.981798 0.981787 0.981792 16087\n", "\n", "Classification report for turbine 21, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.991556 0.987218 0.989382 14630\n", " 20 0.877055 0.915580 0.895903 1457\n", "\n", "avg / total 0.981185 0.980730 0.980916 16087\n", "\n", "Classification report for turbine 21, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.972384 0.994923 0.983524 13590\n", " 20 0.968378 0.846215 0.903184 2497\n", "\n", "avg / total 0.971762 0.971841 0.971054 16087\n", "\n", "Classification report for turbine 21, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.995601 0.996190 0.995896 15223\n", " 20 0.932164 0.922454 0.927283 864\n", "\n", "avg / total 0.992194 0.992230 0.992211 16087\n", "\n", "Classification report for turbine 21, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.994671 0.996796 0.995732 14979\n", " 20 0.955390 0.927798 0.941392 1108\n", "\n", "avg / total 0.991965 0.992043 0.991989 16087\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 21, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.991812 0.987220 0.989511 15337\n", " 20 0.761267 0.833333 0.795672 750\n", "\n", "avg / total 0.981064 0.980046 0.980474 16087\n", "\n", "Classification report for turbine 21, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.992170 0.987355 0.989756 14630\n", " 20 0.878927 0.921757 0.899832 1457\n", "\n", "avg / total 0.981913 0.981414 0.981612 16087\n", "\n", "Classification report for turbine 21, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.960415 0.994408 0.977116 13590\n", " 20 0.962302 0.776932 0.859739 2497\n", "\n", "avg / total 0.960708 0.960651 0.958897 16087\n", "\n", "Classification report for turbine 21, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 9\n", " 11 0.000000 0.000000 0.000000 25\n", " 12 0.000000 0.000000 0.000000 32\n", " 13 0.000000 0.000000 0.000000 27\n", " 14 0.000000 0.000000 0.000000 32\n", " 15 0.000000 0.000000 0.000000 26\n", " 16 0.000000 0.000000 0.000000 21\n", " 17 0.000000 0.000000 0.000000 26\n", " 18 0.000000 0.000000 0.000000 25\n", " 19 0.982149 0.996670 0.989356 15015\n", " 20 0.925882 0.926973 0.926427 849\n", "\n", "avg / total 0.965565 0.979176 0.972320 16087\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and 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with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 22, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 14\n", " 11 0.000000 0.000000 0.000000 86\n", " 12 0.000000 0.000000 0.000000 90\n", " 13 0.000000 0.000000 0.000000 77\n", " 14 0.000000 0.000000 0.000000 87\n", " 15 0.000000 0.000000 0.000000 92\n", " 16 0.000000 0.000000 0.000000 90\n", " 17 0.000000 0.000000 0.000000 88\n", " 18 0.000000 0.000000 0.000000 94\n", " 19 0.951902 0.986274 0.968783 14207\n", " 20 0.817801 0.916129 0.864177 1705\n", "\n", "avg / total 0.897055 0.936500 0.916231 16630\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 22, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.992720 0.985160 0.988926 15364\n", " 20 0.891641 0.909953 0.900704 1266\n", "\n", "avg / total 0.985025 0.979435 0.982209 16630\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 22, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.972881 0.971264 0.972072 14442\n", " 20 0.947398 0.781993 0.856785 2188\n", "\n", "avg / total 0.969528 0.946362 0.956904 16630\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification 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30\n", " 12 0.000000 0.000000 0.000000 28\n", " 13 0.000000 0.000000 0.000000 26\n", " 14 0.000000 0.000000 0.000000 28\n", " 15 0.000000 0.000000 0.000000 27\n", " 16 0.000000 0.000000 0.000000 29\n", " 17 0.000000 0.000000 0.000000 29\n", " 18 0.000000 0.000000 0.000000 26\n", " 19 0.979650 0.989460 0.984531 15180\n", " 20 0.878489 0.873469 0.875972 1225\n", "\n", "avg / total 0.958944 0.967529 0.963214 16630\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 22, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.989430 0.972234 0.980756 14442\n", " 20 0.946536 0.930530 0.938465 2188\n", "\n", "avg / total 0.983786 0.966747 0.975192 16630\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 22, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.992774 0.992151 0.992462 15925\n", " 20 0.931854 0.834043 0.880240 705\n", "\n", "avg / total 0.990192 0.985448 0.987705 16630\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 22, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 4\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 35\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 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"Classification report for turbine 22, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.993546 0.991929 0.992737 15364\n", " 20 0.903950 0.921801 0.912788 1266\n", "\n", "avg / total 0.986725 0.986590 0.986651 16630\n", "\n", "Classification report for turbine 22, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.983329 0.992453 0.987870 14442\n", " 20 0.946933 0.888940 0.917020 2188\n", "\n", "avg / total 0.978540 0.978833 0.978548 16630\n", "\n", "Classification report for turbine 22, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.996174 0.997300 0.996737 15925\n", " 20 0.937409 0.913475 0.925287 705\n", "\n", "avg / total 0.993683 0.993746 0.993708 16630\n", "\n", "Classification report for turbine 22, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.997031 0.995799 0.996415 16188\n", " 20 0.852814 0.891403 0.871681 442\n", "\n", "avg / total 0.993198 0.993025 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"\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.983886 0.968148 0.975954 14442\n", " 20 0.929366 0.877971 0.902938 2188\n", "\n", "avg / total 0.976713 0.956284 0.966347 16630\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 22, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.994072 0.989827 0.991945 15925\n", " 20 0.901173 0.763121 0.826421 705\n", "\n", "avg / total 0.990134 0.980216 0.984928 16630\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 22, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 34\n", " 11 0.000000 0.000000 0.000000 72\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 71\n", " 19 0.959018 0.986862 0.972741 15603\n", " 20 0.802956 0.779904 0.791262 418\n", "\n", "avg / total 0.919976 0.945520 0.932557 16630\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 22, turbine category 9.0\n", " precision recall f1-score 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precision recall f1-score support\n", "\n", " 19 0.996722 0.995490 0.996106 16188\n", " 20 0.841991 0.880090 0.860619 442\n", "\n", "avg / total 0.992609 0.992423 0.992505 16630\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 22, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.115681 0.104167 0.109622 432\n", " 11 0.046980 0.087500 0.061135 240\n", " 12 0.011976 0.010204 0.011019 196\n", " 13 0.023256 0.022099 0.022663 181\n", " 14 0.000000 0.000000 0.000000 157\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.006250 0.008333 0.007143 120\n", " 17 0.000000 0.000000 0.000000 115\n", " 18 0.000000 0.000000 0.000000 105\n", " 19 0.919844 0.840314 0.878282 13752\n", " 20 0.612466 0.738562 0.669630 1224\n", "\n", "avg / total 0.809856 0.753638 0.779730 16630\n", "\n", "Classification report for turbine 22, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.991153 0.969865 0.980393 15364\n", " 20 0.897638 0.720379 0.799299 1266\n", "\n", "avg / total 0.984034 0.950872 0.966607 16630\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 22, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.983427 0.957347 0.970212 14442\n", " 20 0.940778 0.508227 0.659941 2188\n", "\n", "avg / total 0.977816 0.898256 0.929389 16630\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 22, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.055556 0.004049 0.007547 247\n", " 11 0.013158 0.017544 0.015038 57\n", " 12 0.033333 0.018868 0.024096 53\n", " 13 0.000000 0.000000 0.000000 55\n", " 14 0.000000 0.000000 0.000000 46\n", " 15 0.000000 0.000000 0.000000 45\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 20\n", " 18 0.000000 0.000000 0.000000 28\n", " 19 0.981784 0.986731 0.984251 15676\n", " 20 0.426883 0.787466 0.553640 367\n", "\n", "avg / total 0.935860 0.947685 0.940247 16630\n", "\n", "Classification report for turbine 22, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.996176 0.981591 0.988830 16188\n", " 20 0.838384 0.751131 0.792363 442\n", "\n", "avg / total 0.991982 0.975466 0.983608 16630\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 22, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.065025 0.464789 0.114088 142\n", " 11 0.144737 0.068750 0.093220 160\n", " 12 0.022727 0.006757 0.010417 148\n", " 13 0.078947 0.044118 0.056604 136\n", " 14 0.000000 0.000000 0.000000 123\n", " 15 0.000000 0.000000 0.000000 111\n", " 16 0.000000 0.000000 0.000000 113\n", " 17 0.000000 0.000000 0.000000 117\n", " 18 0.000000 0.000000 0.000000 115\n", " 19 0.939333 0.938593 0.938963 13956\n", " 20 0.688973 0.484427 0.568872 1509\n", "\n", "avg / total 0.853607 0.836681 0.842029 16630\n", "\n", "Classification report for turbine 22, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.370130 0.365385 0.367742 312\n", " 11 0.022124 0.014045 0.017182 356\n", " 12 0.004739 0.003774 0.004202 265\n", " 13 0.000000 0.000000 0.000000 190\n", " 14 0.014706 0.007752 0.010152 129\n", " 15 0.000000 0.000000 0.000000 112\n", " 16 0.000000 0.000000 0.000000 112\n", " 17 0.000000 0.000000 0.000000 119\n", " 18 0.000000 0.000000 0.000000 112\n", " 19 0.892153 0.918363 0.905068 13854\n", " 20 0.804746 0.697848 0.747495 1069\n", "\n", "avg / total 0.802566 0.817198 0.809451 16630\n", "\n", "Classification report for turbine 22, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.123779 0.730769 0.211699 52\n", " 11 0.000000 0.000000 0.000000 54\n", " 12 0.023256 0.018519 0.020619 54\n", " 13 0.025641 0.016129 0.019802 62\n", " 14 0.003876 0.017857 0.006369 56\n", " 15 0.000000 0.000000 0.000000 55\n", " 16 0.000000 0.000000 0.000000 56\n", " 17 0.000000 0.000000 0.000000 64\n", " 18 0.000000 0.000000 0.000000 57\n", " 19 0.947125 0.952269 0.949690 13995\n", " 20 0.955975 0.715294 0.818304 2125\n", "\n", "avg / total 0.919781 0.895250 0.904601 16630\n", "\n", "Classification report for turbine 22, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.238095 0.074627 0.113636 134\n", " 11 0.000000 0.000000 0.000000 30\n", " 12 0.000000 0.000000 0.000000 30\n", " 13 0.000000 0.000000 0.000000 28\n", " 14 0.000000 0.000000 0.000000 28\n", " 15 0.000000 0.000000 0.000000 24\n", " 16 0.000000 0.000000 0.000000 22\n", " 17 0.000000 0.000000 0.000000 21\n", " 18 0.000000 0.000000 0.000000 27\n", " 19 0.977356 0.972318 0.974830 15714\n", " 20 0.734940 0.746503 0.740676 572\n", "\n", "avg / total 0.950719 0.945039 0.947527 16630\n", "\n", "Classification report for turbine 22, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 4\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 35\n", " 13 0.031250 0.028571 0.029851 35\n", " 14 0.005814 0.027778 0.009615 36\n", " 15 0.000000 0.000000 0.000000 35\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.500000 0.055556 0.100000 36\n", " 19 0.976869 0.974657 0.975762 15902\n", " 20 0.800570 0.640091 0.711392 439\n", "\n", "avg / total 0.956399 0.949128 0.952126 16630\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 22, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 101\n", " 11 0.000000 0.000000 0.000000 84\n", " 12 0.000000 0.000000 0.000000 60\n", " 13 0.000000 0.000000 0.000000 58\n", " 14 0.000000 0.000000 0.000000 62\n", " 15 0.000000 0.000000 0.000000 58\n", " 16 0.090909 0.015152 0.025974 66\n", " 17 0.000000 0.000000 0.000000 55\n", " 18 0.000000 0.000000 0.000000 57\n", " 19 0.954007 0.971465 0.962657 14263\n", " 20 0.856610 0.909966 0.882482 1766\n", "\n", "avg / total 0.909548 0.929886 0.919456 16630\n", "\n", "Classification report for turbine 22, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.250000 0.030418 0.054237 263\n", " 11 0.000000 0.000000 0.000000 246\n", " 12 0.000000 0.000000 0.000000 243\n", " 13 0.000000 0.000000 0.000000 234\n", " 14 0.050000 0.003876 0.007194 258\n", " 15 0.000000 0.000000 0.000000 243\n", " 16 0.000000 0.000000 0.000000 247\n", " 17 0.000000 0.000000 0.000000 229\n", " 18 0.000000 0.000000 0.000000 230\n", " 19 0.869628 0.980821 0.921884 13452\n", " 20 0.693959 0.886294 0.778422 985\n", "\n", "avg / total 0.749275 0.846422 0.792787 16630\n", "\n", "Classification report for turbine 22, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 10\n", " 11 0.000000 0.000000 0.000000 24\n", " 12 0.000000 0.000000 0.000000 30\n", " 13 0.000000 0.000000 0.000000 27\n", " 14 0.000000 0.000000 0.000000 29\n", " 15 0.000000 0.000000 0.000000 42\n", " 16 0.000000 0.000000 0.000000 52\n", " 17 0.000000 0.000000 0.000000 50\n", " 18 0.000000 0.000000 0.000000 52\n", " 19 0.964931 0.967388 0.966158 14136\n", " 20 0.933171 0.878329 0.904920 2178\n", "\n", "avg / total 0.942436 0.937342 0.939779 16630\n", "\n", "Classification report for turbine 22, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.228916 0.441860 0.301587 43\n", " 11 0.000000 0.000000 0.000000 68\n", " 12 0.000000 0.000000 0.000000 70\n", " 13 0.000000 0.000000 0.000000 64\n", " 14 0.000000 0.000000 0.000000 69\n", " 15 0.000000 0.000000 0.000000 43\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.017857 0.027778 0.021739 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.967002 0.979797 0.973358 15493\n", " 20 0.869932 0.766369 0.814873 672\n", "\n", "avg / total 0.936671 0.944979 0.940564 16630\n", "\n", "Classification report for turbine 22, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 5\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 35\n", " 15 0.000000 0.000000 0.000000 35\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.978303 0.983963 0.981125 15901\n", " 20 0.833713 0.835616 0.834664 438\n", "\n", "avg / total 0.957376 0.962838 0.960099 16630\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 22, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 20\n", " 11 0.043478 0.008929 0.014815 112\n", " 12 0.000000 0.000000 0.000000 101\n", " 13 0.000000 0.000000 0.000000 119\n", " 14 0.000000 0.000000 0.000000 119\n", " 15 0.000000 0.000000 0.000000 106\n", " 16 0.000000 0.000000 0.000000 115\n", " 17 0.000000 0.000000 0.000000 118\n", " 18 0.000000 0.000000 0.000000 115\n", " 19 0.936069 0.980930 0.957974 14001\n", " 20 0.839566 0.909038 0.872922 1704\n", "\n", "avg / total 0.874407 0.919062 0.896074 16630\n", "\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 22, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 6\n", " 11 0.000000 0.000000 0.000000 30\n", " 12 0.000000 0.000000 0.000000 29\n", " 13 0.000000 0.000000 0.000000 30\n", " 14 0.000000 0.000000 0.000000 28\n", " 15 0.000000 0.000000 0.000000 30\n", " 16 0.000000 0.000000 0.000000 27\n", " 17 0.000000 0.000000 0.000000 24\n", " 18 0.000000 0.000000 0.000000 27\n", " 19 0.974583 0.980054 0.977311 15141\n", " 20 0.881536 0.857711 0.869460 1258\n", "\n", "avg / total 0.954007 0.957186 0.955577 16630\n", "\n", "Classification report for turbine 22, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 13\n", " 11 0.000000 0.000000 0.000000 83\n", " 12 0.000000 0.000000 0.000000 86\n", " 13 0.000000 0.000000 0.000000 88\n", " 14 0.000000 0.000000 0.000000 87\n", " 15 0.000000 0.000000 0.000000 80\n", " 16 0.000000 0.000000 0.000000 83\n", " 17 0.000000 0.000000 0.000000 86\n", " 18 0.000000 0.000000 0.000000 90\n", " 19 0.937802 0.970039 0.953648 13818\n", " 20 0.924378 0.878072 0.900630 2116\n", "\n", "avg / total 0.896845 0.917739 0.906990 16630\n", "\n", "Classification report for turbine 22, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 1.000000 0.052632 0.100000 19\n", " 11 0.000000 0.000000 0.000000 86\n", " 12 0.000000 0.000000 0.000000 89\n", " 13 0.000000 0.000000 0.000000 90\n", " 14 0.000000 0.000000 0.000000 89\n", " 15 0.000000 0.000000 0.000000 82\n", " 16 0.000000 0.000000 0.000000 97\n", " 17 0.000000 0.000000 0.000000 86\n", " 18 0.000000 0.000000 0.000000 98\n", " 19 0.952342 0.989479 0.970555 15207\n", " 20 0.878084 0.880640 0.879360 687\n", "\n", "avg / total 0.908269 0.941251 0.923948 16630\n", "\n", "Classification report for turbine 22, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.995165 0.978935 0.986983 16188\n", " 20 0.845433 0.816742 0.830840 442\n", "\n", "avg / total 0.991185 0.974624 0.982833 16630\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 22, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.990137 0.984445 0.987283 14786\n", " 20 0.880767 0.921367 0.900610 1844\n", "\n", "avg / total 0.978009 0.977450 0.977672 16630\n", "\n", "Classification report for turbine 22, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.993543 0.991539 0.992540 15364\n", " 20 0.899769 0.921801 0.910652 1266\n", "\n", "avg / total 0.986405 0.986230 0.986306 16630\n", "\n", "Classification report for turbine 22, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.989614 0.989683 0.989649 14442\n", " 20 0.931870 0.931444 0.931657 2188\n", "\n", "avg / total 0.982017 0.982020 0.982019 16630\n", "\n", "Classification report for turbine 22, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.995795 0.996421 0.996108 15925\n", " 20 0.917986 0.904965 0.911429 705\n", "\n", "avg / total 0.992497 0.992544 0.992518 16630\n", "\n", "Classification report for turbine 22, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.996658 0.994935 0.995796 16188\n", " 20 0.825532 0.877828 0.850877 442\n", "\n", "avg / total 0.992110 0.991822 0.991944 16630\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 22, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.991157 0.985459 0.988300 14786\n", " 20 0.888543 0.929501 0.908561 1844\n", "\n", "avg / total 0.979779 0.979254 0.979458 16630\n", "\n", "Classification report for turbine 22, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.992188 0.991994 0.992091 15364\n", " 20 0.903073 0.905213 0.904142 1266\n", "\n", "avg / total 0.985404 0.985388 0.985396 16630\n", "\n", "Classification report for turbine 22, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.990326 0.992383 0.991354 14442\n", " 20 0.949027 0.936015 0.942476 2188\n", "\n", "avg / total 0.984892 0.984967 0.984923 16630\n", "\n", "Classification report for turbine 22, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 9\n", " 11 0.000000 0.000000 0.000000 28\n", " 12 0.000000 0.000000 0.000000 32\n", " 13 0.000000 0.000000 0.000000 30\n", " 14 0.000000 0.000000 0.000000 29\n", " 15 0.000000 0.000000 0.000000 27\n", " 16 0.000000 0.000000 0.000000 17\n", " 17 0.000000 0.000000 0.000000 17\n", " 18 0.000000 0.000000 0.000000 20\n", " 19 0.983306 0.996312 0.989766 15726\n", " 20 0.902299 0.903597 0.902948 695\n", "\n", "avg / total 0.967563 0.979916 0.973699 16630\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 22, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 19 0.995981 0.995182 0.995581 16188\n", " 20 0.847191 0.852941 0.850056 442\n", "\n", "avg / total 0.992027 0.991401 0.991714 16630\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 23, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 19 0.980078 0.987554 0.983802 14945\n", " 20 0.829044 0.750416 0.787773 1202\n", "\n", "avg / total 0.968835 0.969902 0.969210 16147\n", "\n", "Classification report for turbine 23, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 19 0.973896 0.986194 0.980007 11879\n", " 20 0.960175 0.926429 0.943000 4268\n", "\n", "avg / total 0.970270 0.970397 0.970225 16147\n", "\n", "Classification report for turbine 23, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 19 0.974597 0.993141 0.983781 13559\n", " 20 0.960086 0.864374 0.909719 2588\n", "\n", "avg / total 0.972271 0.972503 0.971911 16147\n", "\n", "Classification report for turbine 23, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 19 0.995723 0.995214 0.995468 15672\n", " 20 0.844720 0.858947 0.851775 475\n", "\n", "avg / total 0.991281 0.991206 0.991241 16147\n", "\n", "Classification report for turbine 23, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 19 0.995195 0.994291 0.994743 15415\n", " 20 0.882038 0.898907 0.890392 732\n", "\n", "avg / total 0.990065 0.989967 0.990012 16147\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 23, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 19 0.984245 0.986484 0.985363 14945\n", " 20 0.827055 0.803661 0.815190 1202\n", "\n", "avg / total 0.972543 0.972874 0.972695 16147\n", "\n", "Classification report for turbine 23, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 19 0.972937 0.986615 0.979728 11879\n", " 20 0.961229 0.923618 0.942048 4268\n", "\n", "avg / total 0.969842 0.969963 0.969769 16147\n", "\n", "Classification report for turbine 23, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 19 0.974444 0.992699 0.983487 13559\n", " 20 0.957584 0.863601 0.908167 2588\n", "\n", "avg / total 0.971742 0.972007 0.971415 16147\n", "\n", "Classification report for turbine 23, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 19 0.996229 0.994449 0.995338 15672\n", " 20 0.827038 0.875789 0.850716 475\n", "\n", "avg / total 0.991251 0.990958 0.991083 16147\n", "\n", "Classification report for turbine 23, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 19 0.994546 0.993707 0.994127 15415\n", " 20 0.869799 0.885246 0.877454 732\n", "\n", "avg / total 0.988891 0.988790 0.988837 16147\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 23, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.981104 0.986685 0.983887 14945\n", " 20 0.821844 0.763727 0.791721 1202\n", "\n", "avg / total 0.969249 0.970087 0.969582 16147\n", "\n", "Classification report for turbine 23, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.985003 0.989730 0.987361 11879\n", " 20 0.971028 0.958060 0.964501 4268\n", "\n", "avg / total 0.981309 0.981359 0.981318 16147\n", "\n", "Classification report for turbine 23, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.979830 0.992404 0.986077 13559\n", " 20 0.957332 0.892968 0.924030 2588\n", "\n", "avg / total 0.976224 0.976466 0.976132 16147\n", "\n", "Classification report for turbine 23, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.995282 0.995980 0.995631 15672\n", " 20 0.864224 0.844211 0.854100 475\n", "\n", "avg / total 0.991426 0.991515 0.991467 16147\n", "\n", "Classification report for turbine 23, turbine category 4.0\n", " precision recall f1-score support\n", "\n", " 19 0.995061 0.993383 0.994222 15415\n", " 20 0.865435 0.896175 0.880537 732\n", "\n", "avg / total 0.989185 0.988976 0.989068 16147\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 23, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 19 0.984901 0.986417 0.985658 14945\n", " 20 0.827820 0.811980 0.819824 1202\n", "\n", "avg / total 0.973208 0.973432 0.973313 16147\n", "\n", "Classification report for turbine 23, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 80\n", " 11 0.000000 0.000000 0.000000 167\n", " 12 0.000000 0.000000 0.000000 154\n", " 13 0.000000 0.000000 0.000000 166\n", " 14 0.000000 0.000000 0.000000 114\n", " 15 0.000000 0.000000 0.000000 105\n", " 16 0.000000 0.000000 0.000000 116\n", " 17 0.000000 0.000000 0.000000 109\n", " 18 0.000000 0.000000 0.000000 106\n", " 19 0.870882 0.986914 0.925275 10928\n", " 20 0.926920 0.850317 0.886968 4102\n", "\n", "avg / total 0.824873 0.883941 0.851535 16147\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 23, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.400000 0.008969 0.017544 223\n", " 11 0.000000 0.000000 0.000000 105\n", " 12 0.000000 0.000000 0.000000 104\n", " 13 0.000000 0.000000 0.000000 110\n", " 14 0.000000 0.000000 0.000000 104\n", " 15 0.000000 0.000000 0.000000 101\n", " 16 0.000000 0.000000 0.000000 105\n", " 17 0.000000 0.000000 0.000000 75\n", " 18 0.000000 0.000000 0.000000 70\n", " 19 0.914126 0.987640 0.949462 12783\n", " 20 0.864615 0.831010 0.847480 2367\n", "\n", "avg / total 0.855950 0.903821 0.876130 16147\n", "\n", "Classification report for turbine 23, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.030769 0.017857 0.022599 112\n", " 11 0.000000 0.000000 0.000000 68\n", " 12 0.000000 0.000000 0.000000 61\n", " 13 0.000000 0.000000 0.000000 65\n", " 14 0.000000 0.000000 0.000000 67\n", " 15 0.080000 0.029851 0.043478 67\n", " 16 0.015152 0.015152 0.015152 66\n", " 17 0.000000 0.000000 0.000000 64\n", " 18 0.000000 0.000000 0.000000 63\n", " 19 0.960553 0.979491 0.969929 15115\n", " 20 0.648585 0.689223 0.668287 399\n", "\n", "avg / total 0.915795 0.934229 0.924851 16147\n", "\n", "Classification report for turbine 23, turbine category 5.0\n", " precision recall f1-score 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category 6.0\n", " precision recall f1-score support\n", "\n", " 19 0.982626 0.983941 0.983283 14945\n", " 20 0.796954 0.783694 0.790268 1202\n", "\n", "avg / total 0.968805 0.969034 0.968915 16147\n", "\n", "Classification report for turbine 23, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 19 0.973112 0.984090 0.978570 11879\n", " 20 0.954282 0.924321 0.939062 4268\n", "\n", "avg / total 0.968135 0.968291 0.968127 16147\n", "\n", "Classification report for turbine 23, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 19 0.975785 0.992625 0.984133 13559\n", " 20 0.957519 0.870943 0.912181 2588\n", "\n", "avg / total 0.972857 0.973122 0.972601 16147\n", "\n", "Classification report for turbine 23, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 79\n", " 11 0.000000 0.000000 0.000000 46\n", " 12 0.000000 0.000000 0.000000 29\n", " 13 0.000000 0.000000 0.000000 34\n", " 14 0.000000 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25\n", " 18 0.000000 0.000000 0.000000 25\n", " 19 0.959631 0.963090 0.961357 11650\n", " 20 0.955047 0.792214 0.866043 4264\n", "\n", "avg / total 0.944654 0.904193 0.922412 16147\n", "\n", "Classification report for turbine 23, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 4\n", " 11 0.000000 0.000000 0.000000 24\n", " 12 0.000000 0.000000 0.000000 22\n", " 13 0.000000 0.000000 0.000000 26\n", " 14 0.000000 0.000000 0.000000 30\n", " 15 0.000000 0.000000 0.000000 26\n", " 16 0.000000 0.000000 0.000000 30\n", " 17 0.000000 0.000000 0.000000 27\n", " 18 0.000000 0.000000 0.000000 21\n", " 19 0.966700 0.947806 0.957160 13354\n", " 20 0.936567 0.680217 0.788069 2583\n", "\n", "avg / total 0.949307 0.892674 0.917662 16147\n", "\n", "Classification report for turbine 23, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 4\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 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"------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 23, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 171\n", " 11 0.000000 0.000000 0.000000 32\n", " 12 0.000000 0.000000 0.000000 25\n", " 13 0.000000 0.000000 0.000000 25\n", " 14 0.000000 0.000000 0.000000 22\n", " 15 0.000000 0.000000 0.000000 28\n", " 16 0.000000 0.000000 0.000000 31\n", " 17 0.000000 0.000000 0.000000 25\n", " 18 0.000000 0.000000 0.000000 26\n", " 19 0.967526 0.971074 0.969296 14727\n", " 20 0.585025 0.445411 0.505760 1035\n", "\n", "avg / total 0.919939 0.914226 0.916473 16147\n", "\n", "Classification report for turbine 23, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.906278 0.309949 0.461920 3307\n", " 11 0.000000 0.000000 0.000000 25\n", " 12 0.000000 0.000000 0.000000 20\n", " 13 0.000000 0.000000 0.000000 30\n", " 14 0.000000 0.000000 0.000000 25\n", " 15 0.003663 0.041667 0.006734 24\n", " 16 0.000000 0.000000 0.000000 22\n", " 17 0.000000 0.000000 0.000000 27\n", " 18 0.000000 0.000000 0.000000 27\n", " 19 0.942089 0.932206 0.937121 11535\n", " 20 0.297523 0.804525 0.434400 1105\n", "\n", "avg / total 0.878981 0.784542 0.793797 16147\n", "\n", "Classification report for turbine 23, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.001497 0.022727 0.002809 44\n", " 11 0.000000 0.000000 0.000000 25\n", " 12 0.000000 0.000000 0.000000 22\n", " 13 0.000000 0.000000 0.000000 23\n", " 14 0.000000 0.000000 0.000000 22\n", " 15 0.000000 0.000000 0.000000 31\n", " 16 0.000000 0.000000 0.000000 17\n", " 17 0.000000 0.000000 0.000000 21\n", " 18 0.000000 0.000000 0.000000 23\n", " 19 0.937825 0.970991 0.954120 13375\n", " 20 0.899035 0.476022 0.622462 2544\n", "\n", "avg / total 0.918475 0.879358 0.888401 16147\n", "\n", "Classification report for turbine 23, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.993770 0.987366 0.990558 15672\n", " 20 0.794416 0.658947 0.720368 475\n", "\n", "avg / total 0.987906 0.977705 0.982610 16147\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program 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"name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 23, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 19 0.980651 0.980060 0.980355 14945\n", " 20 0.775701 0.759567 0.767549 1202\n", "\n", "avg / total 0.965394 0.963646 0.964514 16147\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no 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"name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 23, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 4\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.200000 0.027778 0.048780 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 34\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.976248 0.993696 0.984895 15387\n", " 20 0.842572 0.808511 0.825190 470\n", "\n", "avg / total 0.955270 0.970521 0.962666 16147\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 23, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.992212 0.991826 0.992019 15415\n", " 20 0.876791 0.836066 0.855944 732\n", "\n", "avg / total 0.986980 0.984765 0.985850 16147\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 23, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.121212 0.190476 0.148148 21\n", " 11 0.029126 0.050420 0.036923 119\n", " 12 0.040984 0.045045 0.042918 111\n", " 13 0.022727 0.017391 0.019704 115\n", " 14 0.000000 0.000000 0.000000 113\n", " 15 0.000000 0.000000 0.000000 118\n", " 16 0.000000 0.000000 0.000000 106\n", " 17 0.000000 0.000000 0.000000 110\n", " 18 0.000000 0.000000 0.000000 119\n", " 19 0.933263 0.939214 0.936229 14115\n", " 20 0.720751 0.767273 0.743285 1100\n", "\n", "avg / total 0.865734 0.874342 0.869946 16147\n", "\n", "Classification report for turbine 23, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 7\n", " 11 0.000000 0.000000 0.000000 29\n", " 12 0.000000 0.000000 0.000000 31\n", " 13 0.000000 0.000000 0.000000 23\n", " 14 0.000000 0.000000 0.000000 25\n", " 15 0.000000 0.000000 0.000000 19\n", " 16 0.000000 0.000000 0.000000 26\n", " 17 0.000000 0.000000 0.000000 26\n", " 18 0.000000 0.000000 0.000000 25\n", " 19 0.967441 0.969928 0.968683 11672\n", " 20 0.955090 0.897749 0.925532 4264\n", "\n", "avg / total 0.951538 0.938193 0.944630 16147\n", "\n", "Classification report for turbine 23, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 16\n", " 11 0.047619 0.011236 0.018182 89\n", " 12 0.019231 0.025974 0.022099 77\n", " 13 0.000000 0.000000 0.000000 84\n", " 14 0.000000 0.000000 0.000000 80\n", " 15 0.000000 0.000000 0.000000 73\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 78\n", " 18 0.000000 0.000000 0.000000 81\n", " 19 0.942183 0.953323 0.947720 12940\n", " 20 0.932438 0.895972 0.913841 2557\n", "\n", "avg / total 0.903066 0.906051 0.904410 16147\n", "\n", "Classification report for turbine 23, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.500000 0.055556 0.100000 18\n", " 11 0.000000 0.000000 0.000000 102\n", " 12 0.000000 0.000000 0.000000 95\n", " 13 0.000000 0.000000 0.000000 98\n", " 14 0.000000 0.000000 0.000000 93\n", " 15 0.000000 0.000000 0.000000 97\n", " 16 0.000000 0.000000 0.000000 101\n", " 17 0.000000 0.000000 0.000000 104\n", " 18 0.000000 0.000000 0.000000 102\n", " 19 0.945097 0.983418 0.963877 14896\n", " 20 0.784580 0.784580 0.784580 441\n", "\n", "avg / total 0.893860 0.928717 0.910739 16147\n", "\n", "Classification report for turbine 23, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.500000 0.071429 0.125000 14\n", " 11 0.000000 0.000000 0.000000 71\n", " 12 0.076923 0.014085 0.023810 71\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 71\n", " 16 0.000000 0.000000 0.000000 71\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.955961 0.976991 0.966362 14864\n", " 20 0.875923 0.850789 0.863173 697\n", "\n", "avg / total 0.918584 0.936211 0.927050 16147\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 23, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.983378 0.985681 0.984528 14945\n", " 20 0.816624 0.792845 0.804559 1202\n", "\n", "avg / total 0.970964 0.971326 0.971131 16147\n", "\n", "Classification report for turbine 23, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.966289 0.984510 0.975315 11879\n", " 20 0.954500 0.904405 0.928778 4268\n", "\n", "avg / total 0.963173 0.963337 0.963014 16147\n", "\n", "Classification report for turbine 23, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.973528 0.992699 0.983020 13559\n", " 20 0.957346 0.858578 0.905276 2588\n", "\n", "avg / total 0.970934 0.971202 0.970559 16147\n", "\n", "Classification report for turbine 23, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.995532 0.995151 0.995341 15672\n", " 20 0.841996 0.852632 0.847280 475\n", "\n", "avg / total 0.991015 0.990958 0.990986 16147\n", "\n", "Classification report for turbine 23, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.994938 0.994486 0.994712 15415\n", " 20 0.884980 0.893443 0.889191 732\n", "\n", "avg / total 0.989953 0.989905 0.989928 16147\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 23, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.982202 0.985948 0.984072 14945\n", " 20 0.816594 0.777870 0.796762 1202\n", "\n", "avg / total 0.969874 0.970459 0.970128 16147\n", "\n", "Classification report for turbine 23, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.975482 0.984679 0.980059 11879\n", " 20 0.956208 0.931115 0.943495 4268\n", "\n", "avg / total 0.970387 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"Classification report for turbine 24, turbine category 2.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 19 0.994998 0.993605 0.994301 16418\n", " 20 0.967925 0.925993 0.946494 1108\n", "\n", "avg / total 0.993287 0.989330 0.991279 17526\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 24, turbine category 3.0\n", " precision recall f1-score support\n", "\n", " 19 0.957736 0.996060 0.976522 16244\n", " 20 0.898734 0.443058 0.593521 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"C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 24, turbine category 6.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 65\n", " 11 0.000000 0.000000 0.000000 23\n", " 12 0.000000 0.000000 0.000000 31\n", " 13 0.000000 0.000000 0.000000 30\n", " 14 0.000000 0.000000 0.000000 29\n", " 15 0.000000 0.000000 0.000000 33\n", " 16 0.000000 0.000000 0.000000 30\n", " 17 0.000000 0.000000 0.000000 31\n", " 18 0.000000 0.000000 0.000000 26\n", " 19 0.977978 0.984441 0.981199 16646\n", " 20 0.822669 0.773196 0.797166 582\n", "\n", "avg / total 0.956192 0.960687 0.958404 17526\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program 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0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.760999 0.949105 0.844707 7545\n", " 20 0.990959 0.636910 0.775433 9981\n", "\n", "avg / total 0.891960 0.771311 0.805256 17526\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 24, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 37\n", " 11 0.000000 0.000000 0.000000 98\n", " 12 0.000000 0.000000 0.000000 98\n", " 13 0.066667 0.010870 0.018692 92\n", " 14 0.000000 0.000000 0.000000 100\n", " 15 0.000000 0.000000 0.000000 92\n", " 16 0.142857 0.010204 0.019048 98\n", " 17 0.000000 0.000000 0.000000 95\n", " 18 0.000000 0.000000 0.000000 95\n", " 19 0.948739 0.983343 0.965731 16149\n", " 20 0.799263 0.758741 0.778475 572\n", "\n", "avg / total 0.901432 0.930960 0.915467 17526\n", "\n", "Classification report for turbine 24, turbine category 8.0\n", " precision recall f1-score support\n", "\n", " 10 0.096774 0.005825 0.010989 515\n", " 11 0.000000 0.000000 0.000000 561\n", " 12 0.000000 0.000000 0.000000 534\n", " 13 0.025000 0.001866 0.003472 536\n", " 14 0.000000 0.000000 0.000000 496\n", " 15 0.000000 0.000000 0.000000 498\n", " 16 0.000000 0.000000 0.000000 501\n", " 17 0.480000 0.023857 0.045455 503\n", " 18 0.000000 0.000000 0.000000 502\n", " 19 0.745536 0.985848 0.849015 12366\n", " 20 0.446970 0.803502 0.574409 514\n", "\n", "avg / total 0.556528 0.720073 0.617628 17526\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 24, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 19 0.953921 0.995321 0.974181 16244\n", " 20 0.868284 0.390796 0.538999 1282\n", "\n", "avg / total 0.947656 0.951101 0.942348 17526\n", "\n", "Classification report for turbine 24, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 19 0.940983 0.990630 0.965168 11846\n", " 20 0.978042 0.870423 0.921099 5680\n", "\n", "avg / total 0.952993 0.951672 0.950886 17526\n", "\n", "Classification report for turbine 24, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 19 0.907156 0.982903 0.943511 7545\n", " 20 0.986205 0.923956 0.954066 9981\n", "\n", "avg / total 0.952174 0.949332 0.949522 17526\n", "\n", "Classification report for turbine 24, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 19 0.995032 0.996447 0.995739 16885\n", " 20 0.902755 0.868955 0.885533 641\n", "\n", "avg / total 0.991657 0.991784 0.991708 17526\n", "\n", "Classification report for turbine 24, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 19 0.995865 0.997503 0.996683 16418\n", " 20 0.962072 0.938628 0.950206 1108\n", "\n", "avg / total 0.993729 0.993781 0.993745 17526\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 24, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.196000 0.403292 0.263795 243\n", " 11 0.000000 0.000000 0.000000 149\n", " 12 0.000000 0.000000 0.000000 146\n", " 13 0.019231 0.013514 0.015873 148\n", " 14 0.015385 0.006623 0.009259 151\n", " 15 0.000000 0.000000 0.000000 155\n", " 16 0.017699 0.012903 0.014925 155\n", " 17 0.000000 0.000000 0.000000 158\n", " 18 0.000000 0.000000 0.000000 143\n", " 19 0.882760 0.948194 0.914308 14921\n", " 20 0.806005 0.301642 0.438994 1157\n", "\n", "avg / total 0.807929 0.833048 0.811393 17526\n", "\n", "Classification report for turbine 24, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.001630 0.120000 0.003217 25\n", " 11 0.000000 0.000000 0.000000 97\n", " 12 0.000000 0.000000 0.000000 97\n", " 13 0.000000 0.000000 0.000000 96\n", " 14 0.000000 0.000000 0.000000 95\n", " 15 0.000000 0.000000 0.000000 97\n", " 16 0.000000 0.000000 0.000000 92\n", " 17 0.000000 0.000000 0.000000 96\n", " 18 0.000000 0.000000 0.000000 82\n", " 19 0.843784 0.946296 0.892105 11433\n", " 20 0.874281 0.400301 0.549161 5316\n", "\n", "avg / total 0.815628 0.738902 0.748537 17526\n", "\n", "Classification report for turbine 24, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.029126 0.088235 0.043796 136\n", " 11 0.000000 0.000000 0.000000 78\n", " 12 0.333333 0.040000 0.071429 100\n", " 13 0.000000 0.000000 0.000000 95\n", " 14 0.037037 0.011905 0.018018 84\n", " 15 0.222222 0.023529 0.042553 85\n", " 16 0.000000 0.000000 0.000000 95\n", " 17 0.000000 0.000000 0.000000 95\n", " 18 0.000000 0.000000 0.000000 66\n", " 19 0.750830 0.924172 0.828532 7095\n", " 20 0.953194 0.814838 0.878602 9597\n", "\n", "avg / total 0.829296 0.821408 0.817563 17526\n", "\n", "Classification report for turbine 24, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 26\n", " 11 0.000000 0.000000 0.000000 31\n", " 12 0.000000 0.000000 0.000000 29\n", " 13 0.000000 0.000000 0.000000 28\n", " 14 0.000000 0.000000 0.000000 28\n", " 15 0.000000 0.000000 0.000000 35\n", " 16 0.000000 0.000000 0.000000 27\n", " 17 0.000000 0.000000 0.000000 33\n", " 18 0.043478 0.055556 0.048780 36\n", " 19 0.976453 0.962943 0.969651 16623\n", " 20 0.909627 0.734921 0.812994 630\n", "\n", "avg / total 0.958930 0.939861 0.949016 17526\n", "\n", "Classification report for turbine 24, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.028846 0.096774 0.044444 31\n", " 11 0.000000 0.000000 0.000000 74\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 72\n", " 17 0.000000 0.000000 0.000000 70\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.968914 0.980634 0.974739 15956\n", " 20 0.830693 0.871236 0.850482 963\n", "\n", "avg / total 0.927813 0.940831 0.934231 17526\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 24, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.200000 0.002681 0.005291 746\n", " 11 0.000000 0.000000 0.000000 333\n", " 12 0.000000 0.000000 0.000000 189\n", " 13 0.000000 0.000000 0.000000 181\n", " 14 0.000000 0.000000 0.000000 180\n", " 15 0.000000 0.000000 0.000000 174\n", " 16 0.011905 0.005464 0.007491 183\n", " 17 0.000000 0.000000 0.000000 174\n", " 18 0.000000 0.000000 0.000000 169\n", " 19 0.855414 0.972220 0.910085 14471\n", " 20 0.555369 0.455923 0.500756 726\n", "\n", "avg / total 0.737948 0.821808 0.772492 17526\n", "\n", "Classification report for turbine 24, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.034656 0.245562 0.060739 338\n", " 11 0.000000 0.000000 0.000000 64\n", " 12 0.297872 0.466667 0.363636 60\n", " 13 0.000000 0.000000 0.000000 63\n", " 14 0.000000 0.000000 0.000000 59\n", " 15 0.000000 0.000000 0.000000 64\n", " 16 0.000000 0.000000 0.000000 58\n", " 17 0.000000 0.000000 0.000000 61\n", " 18 0.000000 0.000000 0.000000 58\n", " 19 0.889785 0.955309 0.921383 11434\n", " 20 0.885592 0.430606 0.579458 5267\n", "\n", "avg / total 0.848328 0.758987 0.777670 17526\n", "\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 24, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.890316 0.918754 0.904312 7545\n", " 20 0.990408 0.744815 0.850232 9981\n", "\n", "avg / total 0.947318 0.819696 0.873513 17526\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 24, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.993172 0.973408 0.983191 16885\n", " 20 0.909091 0.702028 0.792254 641\n", "\n", "avg / total 0.990097 0.963483 0.976207 17526\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 24, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.015873 0.007874 0.010526 127\n", " 11 0.358025 0.268519 0.306878 108\n", " 12 0.000000 0.000000 0.000000 107\n", " 13 0.000000 0.000000 0.000000 106\n", " 14 0.000000 0.000000 0.000000 104\n", " 15 0.000000 0.000000 0.000000 105\n", " 16 0.058824 0.009434 0.016260 106\n", " 17 0.000000 0.000000 0.000000 107\n", " 18 0.166667 0.009259 0.017544 108\n", " 19 0.945718 0.990925 0.967794 15648\n", " 20 0.784165 0.803333 0.793633 900\n", "\n", "avg / total 0.888353 0.927822 0.907019 17526\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 24, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.092593 0.037879 0.053763 132\n", " 11 0.000000 0.000000 0.000000 185\n", " 12 0.000000 0.000000 0.000000 173\n", " 13 0.026316 0.006369 0.010256 157\n", " 14 0.000000 0.000000 0.000000 149\n", " 15 0.000000 0.000000 0.000000 140\n", " 16 0.000000 0.000000 0.000000 147\n", " 17 0.000000 0.000000 0.000000 143\n", " 18 0.000000 0.000000 0.000000 141\n", " 19 0.875850 0.963921 0.917777 14967\n", " 20 0.765996 0.351510 0.481886 1192\n", "\n", "avg / total 0.800997 0.847427 0.817043 17526\n", "\n", "Classification report for turbine 24, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.007353 0.021739 0.010989 92\n", " 11 0.000000 0.000000 0.000000 90\n", " 12 0.000000 0.000000 0.000000 83\n", " 13 0.023810 0.011628 0.015625 86\n", " 14 0.000000 0.000000 0.000000 87\n", " 15 0.000000 0.000000 0.000000 100\n", " 16 0.000000 0.000000 0.000000 84\n", " 17 0.000000 0.000000 0.000000 95\n", " 18 0.000000 0.000000 0.000000 96\n", " 19 0.822214 0.977644 0.893217 11093\n", " 20 0.958461 0.669217 0.788139 5620\n", "\n", "avg / total 0.827918 0.833562 0.818222 17526\n", "\n", "Classification report for turbine 24, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.906609 0.941816 0.923877 7545\n", " 20 0.994833 0.925859 0.959107 9981\n", "\n", "avg / total 0.956852 0.932729 0.943941 17526\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 24, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.100000 0.010204 0.018519 98\n", " 11 0.024390 0.009346 0.013514 107\n", " 12 0.000000 0.000000 0.000000 82\n", " 13 0.000000 0.000000 0.000000 72\n", " 14 0.000000 0.000000 0.000000 72\n", " 15 0.000000 0.000000 0.000000 72\n", " 16 0.000000 0.000000 0.000000 71\n", " 17 0.000000 0.000000 0.000000 72\n", " 18 0.000000 0.000000 0.000000 71\n", " 19 0.955160 0.976886 0.965901 16267\n", " 20 0.760000 0.771218 0.765568 542\n", "\n", "avg / total 0.910757 0.930674 0.920376 17526\n", "\n", "Classification report for turbine 24, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.090909 0.006369 0.011905 157\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.000000 0.000000 0.000000 107\n", " 13 0.000000 0.000000 0.000000 107\n", " 14 0.000000 0.000000 0.000000 107\n", " 15 0.000000 0.000000 0.000000 108\n", " 16 0.100000 0.010309 0.018692 97\n", " 17 0.000000 0.000000 0.000000 108\n", " 18 0.000000 0.000000 0.000000 107\n", " 19 0.937718 0.986738 0.961604 15533\n", " 20 0.862845 0.854103 0.858452 987\n", "\n", "avg / total 0.881044 0.922743 0.900808 17526\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 24, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.200000 0.083333 0.117647 36\n", " 11 0.015873 0.009174 0.011628 218\n", " 12 0.000000 0.000000 0.000000 202\n", " 13 0.214286 0.098592 0.135048 213\n", " 14 0.000000 0.000000 0.000000 218\n", " 15 0.000000 0.000000 0.000000 217\n", " 16 0.000000 0.000000 0.000000 220\n", " 17 0.000000 0.000000 0.000000 195\n", " 18 0.000000 0.000000 0.000000 186\n", " 19 0.866226 0.962762 0.911946 14716\n", " 20 0.743219 0.371946 0.495778 1105\n", "\n", "avg / total 0.777413 0.833333 0.799017 17526\n", "\n", "Classification report for turbine 24, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 10\n", " 11 0.000000 0.000000 0.000000 60\n", " 12 0.000000 0.000000 0.000000 57\n", " 13 0.041667 0.016393 0.023529 61\n", " 14 0.038462 0.015625 0.022222 64\n", " 15 0.000000 0.000000 0.000000 67\n", " 16 0.000000 0.000000 0.000000 67\n", " 17 0.000000 0.000000 0.000000 67\n", " 18 0.000000 0.000000 0.000000 63\n", " 19 0.887177 0.976010 0.929476 11505\n", " 20 0.937651 0.773115 0.847471 5505\n", "\n", "avg / total 0.877197 0.883659 0.876515 17526\n", "\n", "Classification report for turbine 24, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.901417 0.935586 0.918184 7545\n", " 20 0.989634 0.918245 0.952604 9981\n", "\n", "avg / total 0.951656 0.925710 0.937786 17526\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 24, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 6\n", " 11 0.017857 0.027778 0.021739 36\n", " 12 0.000000 0.000000 0.000000 33\n", " 13 0.000000 0.000000 0.000000 33\n", " 14 0.000000 0.000000 0.000000 33\n", " 15 0.000000 0.000000 0.000000 35\n", " 16 0.000000 0.000000 0.000000 32\n", " 17 0.000000 0.000000 0.000000 29\n", " 18 0.000000 0.000000 0.000000 28\n", " 19 0.976452 0.980328 0.978386 16623\n", " 20 0.903955 0.752351 0.821215 638\n", "\n", "avg / total 0.959085 0.957263 0.957916 17526\n", "\n", "Classification report for turbine 24, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 19\n", " 11 0.037037 0.009346 0.014925 107\n", " 12 0.000000 0.000000 0.000000 107\n", " 13 0.000000 0.000000 0.000000 97\n", " 14 0.000000 0.000000 0.000000 107\n", " 15 0.000000 0.000000 0.000000 103\n", " 16 0.000000 0.000000 0.000000 103\n", " 17 0.000000 0.000000 0.000000 107\n", " 18 0.000000 0.000000 0.000000 106\n", " 19 0.947523 0.989007 0.967821 15646\n", " 20 0.890518 0.889648 0.890083 1024\n", "\n", "avg / total 0.898140 0.934954 0.916100 17526\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 24, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.958022 0.993290 0.975337 16244\n", " 20 0.840643 0.448518 0.584944 1282\n", "\n", "avg / total 0.949436 0.953441 0.946780 17526\n", "\n", "Classification report for turbine 24, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.893012 0.993500 0.940579 11846\n", " 20 0.982287 0.751761 0.851700 5680\n", "\n", "avg / total 0.921945 0.915155 0.911775 17526\n", "\n", "Classification report for turbine 24, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.927309 0.994168 0.959575 7545\n", " 20 0.995338 0.941088 0.967453 9981\n", "\n", "avg / total 0.966051 0.963939 0.964062 17526\n", "\n", "Classification report for turbine 24, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.994097 0.997335 0.995713 16885\n", " 20 0.923208 0.843994 0.881826 641\n", "\n", "avg / total 0.991504 0.991727 0.991548 17526\n", "\n", "Classification report for turbine 24, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.995017 0.997381 0.996198 16418\n", " 20 0.959775 0.925993 0.942582 1108\n", "\n", "avg / total 0.992789 0.992868 0.992808 17526\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 24, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.954229 0.995937 0.974637 16244\n", " 20 0.884615 0.394696 0.545847 1282\n", "\n", "avg / total 0.949137 0.951957 0.943272 17526\n", "\n", "Classification report for turbine 24, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.889720 0.993669 0.938826 11846\n", " 20 0.982542 0.743134 0.846231 5680\n", "\n", "avg / total 0.919803 0.912473 0.908817 17526\n", "\n", "Classification report for turbine 24, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.923869 0.987541 0.954644 7545\n", " 20 0.990064 0.938483 0.963584 9981\n", "\n", "avg / total 0.961567 0.959603 0.959735 17526\n", "\n", "Classification report for turbine 24, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 16\n", " 11 0.000000 0.000000 0.000000 35\n", " 12 0.000000 0.000000 0.000000 32\n", " 13 0.000000 0.000000 0.000000 27\n", " 14 0.000000 0.000000 0.000000 22\n", " 15 0.000000 0.000000 0.000000 30\n", " 16 0.000000 0.000000 0.000000 26\n", " 17 0.000000 0.000000 0.000000 31\n", " 18 0.000000 0.000000 0.000000 27\n", " 19 0.981382 0.996998 0.989128 16654\n", " 20 0.896211 0.869010 0.882401 626\n", "\n", "avg / total 0.964565 0.978432 0.971432 17526\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 24, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.993206 0.997198 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0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.990188 0.982728 0.986444 16327\n", " 20 0.804455 0.799508 0.801974 813\n", "\n", "avg / total 0.981378 0.974037 0.977694 17140\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 25, turbine category 5.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 92\n", " 11 0.000000 0.000000 0.000000 96\n", " 12 0.000000 0.000000 0.000000 85\n", " 13 0.000000 0.000000 0.000000 99\n", " 14 0.000000 0.000000 0.000000 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15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.990369 0.982544 0.986441 16327\n", " 20 0.793478 0.808118 0.800731 813\n", "\n", "avg / total 0.981030 0.974271 0.977632 17140\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 25, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.991961 0.989393 0.990675 15839\n", " 20 0.914330 0.902383 0.908317 1301\n", "\n", "avg / total 0.986068 0.982789 0.984424 17140\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 25, turbine category 9.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 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0.000000 0.000000 0.000000 31\n", " 16 0.000000 0.000000 0.000000 28\n", " 17 0.000000 0.000000 0.000000 29\n", " 18 0.000000 0.000000 0.000000 31\n", " 19 0.928562 0.965745 0.946789 14509\n", " 20 0.944954 0.604612 0.737407 2385\n", "\n", "avg / total 0.917516 0.901634 0.904065 17140\n", "\n", "Classification report for turbine 25, turbine category 10.0\n", " precision recall f1-score support\n", "\n", " 10 0.010204 0.045455 0.016667 44\n", " 11 0.000000 0.000000 0.000000 66\n", " 12 0.000000 0.000000 0.000000 58\n", " 13 0.000000 0.000000 0.000000 68\n", " 14 0.000000 0.000000 0.000000 64\n", " 15 0.000000 0.000000 0.000000 65\n", " 16 0.000000 0.000000 0.000000 62\n", " 17 0.000000 0.000000 0.000000 56\n", " 18 0.000000 0.000000 0.000000 68\n", " 19 0.954457 0.983958 0.968983 14462\n", " 20 0.938155 0.841561 0.887237 2127\n", "\n", "avg / total 0.921777 0.934772 0.927732 17140\n", "\n", "Classification report for turbine 25, turbine category 10.0\n", " precision recall f1-score 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0.000000 0.000000 0.000000 150\n", " 19 0.899500 0.992067 0.943519 13614\n", " 20 0.760500 0.887916 0.819284 1713\n", "\n", "avg / total 0.802585 0.877363 0.832520 17140\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 25, turbine category 11.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 4\n", " 11 0.000000 0.000000 0.000000 36\n", " 12 0.000000 0.000000 0.000000 36\n", " 13 0.000000 0.000000 0.000000 36\n", " 14 0.000000 0.000000 0.000000 36\n", " 15 0.000000 0.000000 0.000000 36\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.973768 0.994120 0.983839 15646\n", " 20 0.958602 0.866889 0.910441 1202\n", "\n", "avg / total 0.956115 0.968261 0.961931 17140\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 25, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.989487 0.974276 0.981823 16327\n", " 20 0.854025 0.769988 0.809832 813\n", "\n", "avg / total 0.983062 0.964586 0.973665 17140\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 25, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 4\n", " 11 0.000000 0.000000 0.000000 33\n", " 12 0.000000 0.000000 0.000000 31\n", " 13 0.000000 0.000000 0.000000 30\n", " 14 0.000000 0.000000 0.000000 24\n", " 15 0.000000 0.000000 0.000000 35\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 29\n", " 18 0.000000 0.000000 0.000000 28\n", " 19 0.974542 0.987834 0.981143 15617\n", " 20 0.882641 0.850746 0.866400 1273\n", "\n", "avg / total 0.953502 0.963244 0.958310 17140\n", "\n", "Classification report for turbine 25, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 27\n", " 11 0.000000 0.000000 0.000000 47\n", " 12 0.000000 0.000000 0.000000 37\n", " 13 0.000000 0.000000 0.000000 24\n", " 14 0.000000 0.000000 0.000000 32\n", " 15 0.000000 0.000000 0.000000 24\n", " 16 0.000000 0.000000 0.000000 34\n", " 17 0.000000 0.000000 0.000000 32\n", " 18 0.000000 0.000000 0.000000 33\n", " 19 0.939533 0.991985 0.965047 14473\n", " 20 0.958380 0.726546 0.826514 2377\n", "\n", "avg / total 0.926250 0.938390 0.929507 17140\n", "\n", "Classification report for turbine 25, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 116\n", " 11 0.000000 0.000000 0.000000 83\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 70\n", " 14 0.000000 0.000000 0.000000 69\n", " 15 0.000000 0.000000 0.000000 70\n", " 16 0.000000 0.000000 0.000000 69\n", " 17 0.000000 0.000000 0.000000 71\n", " 18 0.000000 0.000000 0.000000 72\n", " 19 0.948337 0.990462 0.968942 14363\n", " 20 0.926972 0.913189 0.920029 2085\n", "\n", "avg / total 0.907450 0.941074 0.923872 17140\n", "\n", "Classification report for turbine 25, turbine category 16.0\n", " precision recall f1-score support\n", "\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.992048 0.994289 0.993167 15934\n", " 20 0.971971 0.891376 0.929931 1206\n", "\n", "avg / total 0.990635 0.987048 0.988718 17140\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 25, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.032258 0.052632 0.040000 19\n", " 11 0.000000 0.000000 0.000000 108\n", " 12 0.000000 0.000000 0.000000 124\n", " 13 0.000000 0.000000 0.000000 122\n", " 14 0.008547 0.007752 0.008130 129\n", " 15 0.000000 0.000000 0.000000 128\n", " 16 0.009346 0.007752 0.008475 129\n", " 17 0.000000 0.000000 0.000000 115\n", " 18 0.007463 0.007937 0.007692 126\n", " 19 0.936331 0.947068 0.941669 15435\n", " 20 0.685637 0.717730 0.701317 705\n", "\n", "avg / total 0.871616 0.882614 0.877069 17140\n", "\n", "Classification report for turbine 25, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 9\n", " 11 0.000000 0.000000 0.000000 60\n", " 12 0.000000 0.000000 0.000000 64\n", " 13 0.000000 0.000000 0.000000 66\n", " 14 0.000000 0.000000 0.000000 55\n", " 15 0.000000 0.000000 0.000000 53\n", " 16 0.008772 0.018182 0.011834 55\n", " 17 0.057692 0.050000 0.053571 60\n", " 18 0.000000 0.000000 0.000000 58\n", " 19 0.966304 0.971772 0.969031 15375\n", " 20 0.901474 0.904280 0.902875 1285\n", "\n", "avg / total 0.934613 0.939732 0.937159 17140\n", "\n", "Classification report for turbine 25, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 6\n", " 11 0.000000 0.000000 0.000000 27\n", " 12 0.000000 0.000000 0.000000 28\n", " 13 0.000000 0.000000 0.000000 31\n", " 14 0.000000 0.000000 0.000000 30\n", " 15 0.000000 0.000000 0.000000 30\n", " 16 0.000000 0.000000 0.000000 29\n", " 17 0.000000 0.000000 0.000000 31\n", " 18 0.000000 0.000000 0.000000 26\n", " 19 0.942522 0.962455 0.952384 14516\n", " 20 0.974473 0.735960 0.838586 2386\n", "\n", "avg / total 0.933882 0.917561 0.923318 17140\n", "\n", "Classification report for turbine 25, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.500000 0.071429 0.125000 14\n", " 11 0.000000 0.000000 0.000000 56\n", " 12 0.000000 0.000000 0.000000 60\n", " 13 0.031250 0.015873 0.021053 63\n", " 14 0.000000 0.000000 0.000000 85\n", " 15 0.000000 0.000000 0.000000 97\n", " 16 0.035714 0.010000 0.015625 100\n", " 17 0.000000 0.000000 0.000000 97\n", " 18 0.000000 0.000000 0.000000 97\n", " 19 0.947945 0.980249 0.963827 14379\n", " 20 0.924528 0.913480 0.918971 2092\n", "\n", "avg / total 0.908819 0.934014 0.921003 17140\n", "\n", "Classification report for turbine 25, turbine category 18.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 12\n", " 11 0.000000 0.000000 0.000000 71\n", " 12 0.000000 0.000000 0.000000 72\n", " 13 0.000000 0.000000 0.000000 60\n", " 14 0.066667 0.021277 0.032258 47\n", " 15 0.000000 0.000000 0.000000 35\n", " 16 0.000000 0.000000 0.000000 36\n", " 17 0.000000 0.000000 0.000000 36\n", " 18 0.000000 0.000000 0.000000 36\n", " 19 0.978362 0.988937 0.983621 15728\n", " 20 0.793230 0.860973 0.825714 1007\n", "\n", "avg / total 0.944550 0.958110 0.951190 17140\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 25, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.991002 0.991609 0.991305 16327\n", " 20 0.829390 0.819188 0.824257 813\n", "\n", "avg / total 0.983336 0.983431 0.983382 17140\n", "\n", "Classification report for turbine 25, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.992499 0.994065 0.993281 15839\n", " 20 0.926332 0.908532 0.917346 1301\n", "\n", "avg / total 0.987476 0.987573 0.987518 17140\n", "\n", "Classification report for turbine 25, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.954209 0.996000 0.974657 14750\n", " 20 0.966170 0.705021 0.815191 2390\n", "\n", "avg / total 0.955877 0.955426 0.952421 17140\n", "\n", "Classification report for turbine 25, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.989488 0.993720 0.991599 14967\n", " 20 0.955429 0.927289 0.941149 2173\n", "\n", "avg / total 0.985170 0.985298 0.985203 17140\n", "\n", "Classification report for turbine 25, turbine category 19.0\n", " precision recall f1-score support\n", "\n", " 19 0.992812 0.996925 0.994864 15934\n", " 20 0.957018 0.904643 0.930094 1206\n", "\n", "avg / total 0.990294 0.990432 0.990307 17140\n", "\n", "------------------------------------------------------------------------\n", "Classification report for turbine 25, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.991908 0.990997 0.991452 16327\n", " 20 0.822464 0.837638 0.829982 813\n", "\n", "avg / total 0.983871 0.983722 0.983793 17140\n", "\n", "Classification report for turbine 25, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.993800 0.991729 0.992763 15839\n", " 20 0.901799 0.924673 0.913093 1301\n", "\n", "avg / total 0.986817 0.986639 0.986716 17140\n", "\n", "Classification report for turbine 25, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 19 0.953605 0.996339 0.974503 14750\n", " 20 0.968768 0.700837 0.813304 2390\n", "\n", "avg / total 0.955719 0.955134 0.952026 17140\n", "\n", "Classification report for turbine 25, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 127\n", " 11 0.000000 0.000000 0.000000 268\n", " 12 0.000000 0.000000 0.000000 260\n", " 13 0.000000 0.000000 0.000000 247\n", " 14 0.000000 0.000000 0.000000 158\n", " 15 0.000000 0.000000 0.000000 136\n", " 16 0.000000 0.000000 0.000000 139\n", " 17 0.000000 0.000000 0.000000 129\n", " 18 0.000000 0.000000 0.000000 133\n", " 19 0.909460 0.995920 0.950728 13727\n", " 20 0.798861 0.927313 0.858308 1816\n", "\n", "avg / total 0.813004 0.895858 0.852353 17140\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1113: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n", " 'precision', 'predicted', average, warn_for)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Classification report for turbine 25, turbine category 20.0\n", " precision recall f1-score support\n", "\n", " 10 0.000000 0.000000 0.000000 0\n", " 11 0.000000 0.000000 0.000000 0\n", " 12 0.000000 0.000000 0.000000 0\n", " 13 0.000000 0.000000 0.000000 0\n", " 14 0.000000 0.000000 0.000000 0\n", " 15 0.000000 0.000000 0.000000 0\n", " 16 0.000000 0.000000 0.000000 0\n", " 17 0.000000 0.000000 0.000000 0\n", " 18 0.000000 0.000000 0.000000 0\n", " 19 0.993438 0.988139 0.990781 15934\n", " 20 0.963370 0.872305 0.915579 1206\n", "\n", "avg / total 0.991322 0.979988 0.985490 17140\n", "\n", "------------------------------------------------------------------------\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "C:\\Program Files\\Anaconda3\\lib\\site-packages\\sklearn\\metrics\\classification.py:1115: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples.\n", " 'recall', 'true', average, warn_for)\n" ] } ], "source": [ "for x in list1: # filter only data for turbine x\n", " dfx = df[(df[\"turbine_id\"] == x)].copy()\n", " for y in list2:\n", " # copying fault to new column (mins)\n", " # (fault when turbine category id is y)\n", "\n", " def ff(c):\n", " if c[\"TurbineCategory_id\"] == y:\n", " return 0\n", " else:\n", " return 1\n", "\n", " dfx[\"mins\"] = dfx.apply(ff, axis=1)\n", "\n", " dfx = dfx.sort_values(by=\"timestamp\", ascending=False)\n", " # sort values by timestamp in descending order\n", " dfx.reset_index(drop=True, inplace=True) # reset index\n", "\n", " if dfx.loc[0, \"mins\"] == 0:\n", " # assigning value to first cell if it's not 0\n", " dfx.set_value(0, \"mins\", 0)\n", " else:\n", " dfx.set_value(0, \"mins\", 999999999)\n", "\n", " for i, e in enumerate(dfx[\"mins\"]):\n", " # using previous value's row to evaluate time\n", " if e == 1:\n", " dfx.at[i, \"mins\"] = dfx.at[i - 1, \"mins\"] + 10\n", "\n", " dfx = dfx.sort_values(by=\"timestamp\") # sort in ascending order\n", " dfx.reset_index(drop=True, inplace=True) # reset index\n", " dfx[\"hours\"] = dfx[\"mins\"].astype(np.int64)\n", " # convert to hours, then round to nearest hour\n", " dfx[\"hours\"] = dfx[\"hours\"] / 60\n", " dfx[\"hours\"] = round(dfx[\"hours\"]).astype(np.int64)\n", "\n", " def f11(c): # >48 hours - label as normal (9999)\n", " if c[\"hours\"] > 48:\n", " return 9999\n", " else:\n", " return c[\"hours\"]\n", "\n", " dfx[\"hours\"] = dfx.apply(f11, axis=1)\n", "\n", " def f22(\n", " c,\n", " ):\n", " # filter out curtailment - curtailed when turbine is\n", " # pitching outside 0 deg <= normal <= 3.5 deg\n", " if (\n", " 0 <= c[\"pitch\"] <= 3.5\n", " or c[\"hours\"] != 9999\n", " or (\n", " (c[\"pitch\"] > 3.5 or c[\"pitch\"] < 0)\n", " and (\n", " c[\"ap_av\"] <= (0.1 * dfx[\"ap_av\"].max())\n", " or c[\"ap_av\"] >= (0.9 * dfx[\"ap_av\"].max())\n", " )\n", " )\n", " ):\n", " return \"normal\"\n", " else:\n", " return \"curtailed\"\n", "\n", " dfx[\"curtailment\"] = dfx.apply(f22, axis=1)\n", "\n", " def f3(\n", " c,\n", " ):\n", " # filter unusual readings, i.e. for normal operation,\n", " # power <= 0 in operating wind speeds, power > 100...\n", " # before cut-in, runtime < 600 and other downtime categories\n", " if c[\"hours\"] == 9999 and (\n", " (\n", " 3 < c[\"ws_av\"] < 25\n", " and (\n", " c[\"ap_av\"] <= 0\n", " or c[\"runtime\"] < 600\n", " or c[\"EnvironmentalCategory_id\"] > 1\n", " or c[\"GridCategory_id\"] > 1\n", " or c[\"InfrastructureCategory_id\"] > 1\n", " or c[\"AvailabilityCategory_id\"] == 2\n", " or 12 <= c[\"TurbineCategory_id\"] <= 15\n", " or 21 <= c[\"TurbineCategory_id\"] <= 22\n", " )\n", " )\n", " or (c[\"ws_av\"] < 3 and c[\"ap_av\"] > 100)\n", " ):\n", " return \"unusual\"\n", " else:\n", " return \"normal\"\n", "\n", " dfx[\"unusual\"] = dfx.apply(f3, axis=1)\n", "\n", " def f4(c): # round to 6 hour intervals\n", " if c[\"hours\"] == 0:\n", " return 10\n", " elif 1 <= c[\"hours\"] <= 6:\n", " return 11\n", " elif 7 <= c[\"hours\"] <= 12:\n", " return 12\n", " elif 13 <= c[\"hours\"] <= 18:\n", " return 13\n", " elif 19 <= c[\"hours\"] <= 24:\n", " return 14\n", " elif 25 <= c[\"hours\"] <= 30:\n", " return 15\n", " elif 31 <= c[\"hours\"] <= 36:\n", " return 16\n", " elif 37 <= c[\"hours\"] <= 42:\n", " return 17\n", " elif 43 <= c[\"hours\"] <= 48:\n", " return 18\n", " else:\n", " return 19\n", "\n", " dfx[\"hours6\"] = dfx.apply(f4, axis=1)\n", "\n", " def f5(c): # change label for unusual and curtailed data (20)\n", " if c[\"unusual\"] == \"unusual\" or c[\"curtailment\"] == \"curtailed\":\n", " return 20\n", " else:\n", " return c[\"hours6\"]\n", "\n", " dfx[\"hours_%s\" % y] = dfx.apply(f5, axis=1)\n", "\n", " dfx = dfx.drop(\"hours6\", axis=1) # drop unnecessary columns\n", " dfx = dfx.drop(\"hours\", axis=1)\n", " dfx = dfx.drop(\"mins\", axis=1)\n", " dfx = dfx.drop(\"curtailment\", axis=1)\n", " dfx = dfx.drop(\"unusual\", axis=1)\n", "\n", " # separate features from classes for classification\n", " features = [\n", " \"ap_av\",\n", " \"ws_av\",\n", " \"wd_av\",\n", " \"pitch\",\n", " \"ap_max\",\n", " \"ap_dev\",\n", " \"reactive_power\",\n", " \"rs_av\",\n", " \"gen_sp\",\n", " \"nac_pos\",\n", " ]\n", " classes = [col for col in dfx.columns if \"hours\" in col]\n", " list6 = features + classes # list of columns to copy into new df\n", " df2 = dfx[list6].copy()\n", " df2 = df2.dropna() # drop NaNs\n", " X = df2[features]\n", " X = preprocessing.normalize(X) # normalise features to values b/w 0 and 1\n", " Y = df2[classes]\n", " Y = Y.as_matrix() # convert from pd dataframe to np array\n", " tscv = TimeSeriesSplit(n_splits=5)\n", " # cross validation using time series split\n", "\n", " rf = RandomForestClassifier(criterion=\"entropy\", n_jobs=-1)\n", " for m, n in list5:\n", " Ym = Y[:, m]\n", " for train_index, test_index in tscv.split(X):\n", " # looping for each cross validation fold\n", " X_train, X_test = X[train_index], X[test_index]\n", " # split train and test sets\n", " Y_train, Y_test = Ym[train_index], Ym[test_index]\n", " if len(set(Y_train)) > 1:\n", " ros = RandomOverSampler()\n", " Xt, Yt = ros.fit_sample(X_train, Y_train)\n", " else:\n", " Xt, Yt = X_train, Y_train\n", " rf1 = rf.fit(Xt, Yt) # fit to classifier and predict\n", " Yp = rf1.predict(X_test)\n", " print(\n", " \"Classification report for turbine %s, turbine category %s\"\n", " % (x, n)\n", " )\n", " print(classification_report(Y_test, Yp, digits=6))\n", " print(\"-------------------------------------------------------------\")\n", "\n", "strftime(\"%Y-%m-%d %H:%M:%S\", gmtime())" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.2" } }, "nbformat": 4, "nbformat_minor": 2 }