10559564 8323 Heinrich Peters 14954 Supervised Classification 18298 sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,columntransformer=sklearn.compose._column_transformer.ColumnTransformer(num=sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler),cat=sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),svc=sklearn.svm.classes.SVC)(4) 8276176 copy true 17405 with_mean true 17405 with_std true 17405 add_indicator false 17407 copy true 17407 fill_value null 17407 missing_values NaN 17407 strategy "most_frequent" 17407 verbose 0 17407 categorical_features null 17408 categories null 17408 drop null 17408 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 17408 handle_unknown "ignore" 17408 n_values null 17408 sparse true 17408 C 1.2019329859336583 17495 cache_size 200 17495 class_weight null 17495 coef0 -0.8056274588169823 17495 decision_function_shape "ovr" 17495 degree 2 17495 gamma 0.14660663245874161 17495 kernel "rbf" 17495 max_iter -1 17495 probability true 17495 random_state 1 17495 shrinking true 17495 tol 0.001 17495 verbose false 17495 memory null 18298 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "svc", "step_name": "svc"}}] 18298 verbose false 18298 n_jobs null 18299 remainder "drop" 18299 sparse_threshold 0.3 18299 transformer_weights null 18299 transformers [{"oml-python:serialized_object": "component_reference", "value": {"key": "num", "step_name": "num", "argument_1": [false, true, false, false, false, false, false, false, false, false, false, false, false, false, true, false, false, false, true, true, false, true, true, true, true, true, true, true, true, true, true, true, true, true, false, true, false]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "cat", "step_name": "cat", "argument_1": [true, false, true, true, true, true, true, true, true, true, true, true, true, true, false, true, true, true, false, false, true, false, false, false, false, false, false, false, false, false, false, false, false, false, true, false, true]}}] 18299 verbose false 18299 memory null 18300 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}] 18300 verbose false 18300 memory null 18301 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}] 18301 verbose false 18301 openml-python Sklearn_0.21.2. 6332 cylinder-bands https://www.openml.org/data/download/1854224/phpAz9Len -1 22044115 description https://api.openml.org/data/download/22044115/description.xml -1 22044116 predictions https://api.openml.org/data/download/22044116/predictions.arff area_under_roc_curve 0.8852760908681961 [0.885276,0.885276] average_cost 0 f_measure 0.8157005525214781 [0.77551,0.84507] kappa 0.6208833290783763 kb_relative_information_score 0.4703727395877963 mean_absolute_error 0.2726122704273149 mean_prior_absolute_error 0.48794587945879536 weighted_recall 0.8166666666666667 [0.75,0.865385] number_of_instances 540 [228,312] precision 0.816031356333721 [0.802817,0.825688] predictive_accuracy 0.8166666666666668 prior_entropy 0.9824743303740947 relative_absolute_error 0.5586936623579699 root_mean_prior_squared_error 0.49391365607219145 root_mean_squared_error 0.36556669691472815 root_relative_squared_error 0.7401429225947463 total_cost 0 unweighted_recall 0.8076923076923077 [0.75,0.865385] area_under_roc_curve 0.9130434782608695 [0.913043,0.913043] area_under_roc_curve 0.9368863955119214 [0.936886,0.936886] area_under_roc_curve 0.9158485273492287 [0.915849,0.915849] area_under_roc_curve 0.758765778401122 [0.758766,0.758766] area_under_roc_curve 0.8611500701262272 [0.86115,0.86115] area_under_roc_curve 0.8260869565217391 [0.826087,0.826087] area_under_roc_curve 0.932678821879383 [0.932679,0.932679] area_under_roc_curve 0.8920056100981767 [0.892006,0.892006] area_under_roc_curve 0.9659090909090908 [0.965909,0.965909] area_under_roc_curve 0.8480113636363638 [0.848011,0.848011] average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 f_measure 0.8888888888888888 [0.869565,0.903226] f_measure 0.8524691358024691 [0.833333,0.866667] f_measure 0.8116081449414784 [0.761905,0.848485] f_measure 0.7564168819982774 [0.697674,0.8] f_measure 0.7761994949494949 [0.727273,0.8125] f_measure 0.7362514029180696 [0.666667,0.787879] f_measure 0.868839859537534 [0.837209,0.892308] f_measure 0.8116081449414784 [0.761905,0.848485] f_measure 0.9070430000662557 [0.883721,0.923077] f_measure 0.7429012345679011 [0.708333,0.766667] kappa 0.7727910238429172 kappa 0.7004160887656034 kappa 0.612625538020086 kappa 0.49928673323823125 kappa 0.5404255319148936 kappa 0.4576757532281205 kappa 0.7303851640513552 kappa 0.612625538020086 kappa 0.8068669527896997 kappa 0.47790055248618774 kb_relative_information_score 0.5739056645914444 kb_relative_information_score 0.5216963285824835 kb_relative_information_score 0.529100866605946 kb_relative_information_score 0.33770434636479885 kb_relative_information_score 0.4794056475414194 kb_relative_information_score 0.37039206125773555 kb_relative_information_score 0.524994533012664 kb_relative_information_score 0.4557223042291978 kb_relative_information_score 0.5432708940882418 kb_relative_information_score 0.3672785991005252 mean_absolute_error 0.22577332776884984 mean_absolute_error 0.24980106215083298 mean_absolute_error 0.2423593814490236 mean_absolute_error 0.33271254225687735 mean_absolute_error 0.2653443462605729 mean_absolute_error 0.3165852271410878 mean_absolute_error 0.2482417845652894 mean_absolute_error 0.28310668337719286 mean_absolute_error 0.24493332009535834 mean_absolute_error 0.3172650292080647 mean_prior_absolute_error 0.48851988519885264 mean_prior_absolute_error 0.48851988519885264 mean_prior_absolute_error 0.48851988519885264 mean_prior_absolute_error 0.48851988519885264 mean_prior_absolute_error 0.48851988519885264 mean_prior_absolute_error 0.48851988519885264 mean_prior_absolute_error 0.48851988519885264 mean_prior_absolute_error 0.48851988519885264 mean_prior_absolute_error 0.4856498564985656 mean_prior_absolute_error 0.4856498564985656 number_of_instances 54 [23,31] number_of_instances 54 [23,31] number_of_instances 54 [23,31] number_of_instances 54 [23,31] number_of_instances 54 [23,31] number_of_instances 54 [23,31] number_of_instances 54 [23,31] number_of_instances 54 [23,31] number_of_instances 54 [22,32] number_of_instances 54 [22,32] precision 0.8888888888888888 [0.869565,0.903226] precision 0.8554278416347382 [0.8,0.896552] precision 0.8179337231968811 [0.842105,0.8] precision 0.7584422657952069 [0.75,0.764706] precision 0.7768157768157766 [0.761905,0.787879] precision 0.7402951824004455 [0.736842,0.742857] precision 0.8729847494553377 [0.9,0.852941] precision 0.8179337231968811 [0.842105,0.8] precision 0.9073272406605739 [0.904762,0.909091] precision 0.7531542531542532 [0.653846,0.821429] predictive_accuracy 0.8888888888888888 predictive_accuracy 0.8518518518518519 predictive_accuracy 0.8148148148148148 predictive_accuracy 0.7592592592592592 predictive_accuracy 0.7777777777777777 predictive_accuracy 0.7407407407407408 predictive_accuracy 0.8703703703703703 predictive_accuracy 0.8148148148148148 predictive_accuracy 0.9074074074074074 predictive_accuracy 0.7407407407407408 prior_entropy 0.9841440157771891 prior_entropy 0.9841440157771891 prior_entropy 0.9841440157771891 prior_entropy 0.9841440157771891 prior_entropy 0.9841440157771891 prior_entropy 0.9841440157771891 prior_entropy 0.9841440157771891 prior_entropy 0.9841440157771891 prior_entropy 0.9757955887617137 prior_entropy 0.9757955887617137 relative_absolute_error 0.46215790719951655 relative_absolute_error 0.5113426693964589 relative_absolute_error 0.49610955212267543 relative_absolute_error 0.6810624343806317 relative_absolute_error 0.5431597654465267 relative_absolute_error 0.6480498271062628 relative_absolute_error 0.5081508288331851 relative_absolute_error 0.5795192620704763 relative_absolute_error 0.5043413826193146 relative_absolute_error 0.6532793636458157 root_mean_prior_squared_error 0.49449439369385695 root_mean_prior_squared_error 0.49449439369385695 root_mean_prior_squared_error 0.49449439369385695 root_mean_prior_squared_error 0.49449439369385695 root_mean_prior_squared_error 0.49449439369385695 root_mean_prior_squared_error 0.49449439369385695 root_mean_prior_squared_error 0.49449439369385695 root_mean_prior_squared_error 0.49449439369385695 root_mean_prior_squared_error 0.4915838450298872 root_mean_prior_squared_error 0.4915838450298872 root_mean_squared_error 0.32920781452950276 root_mean_squared_error 0.32601182560363856 root_mean_squared_error 0.3396060126220193 root_mean_squared_error 0.4438129756552796 root_mean_squared_error 0.3745048293874879 root_mean_squared_error 0.4150966925622921 root_mean_squared_error 0.327891567001283 root_mean_squared_error 0.3672574563720215 root_mean_squared_error 0.30453727724819324 root_mean_squared_error 0.40216091128535403 root_relative_squared_error 0.6657463031488207 root_relative_squared_error 0.6592831582342943 root_relative_squared_error 0.6867742424442338 root_relative_squared_error 0.897508609430354 root_relative_squared_error 0.7573489895202837 root_relative_squared_error 0.8394366000017379 root_relative_squared_error 0.6630844983942967 root_relative_squared_error 0.7426928617504039 root_relative_squared_error 0.6195022076644484 root_relative_squared_error 0.8180922041099693 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 unweighted_recall 0.8863955119214586 [0.869565,0.903226] unweighted_recall 0.8541374474053296 [0.869565,0.83871] unweighted_recall 0.7994389901823282 [0.695652,0.903226] unweighted_recall 0.7454417952314165 [0.652174,0.83871] unweighted_recall 0.7671809256661992 [0.695652,0.83871] unweighted_recall 0.723702664796634 [0.608696,0.83871] unweighted_recall 0.8590462833099579 [0.782609,0.935484] unweighted_recall 0.7994389901823282 [0.695652,0.903226] unweighted_recall 0.9005681818181819 [0.863636,0.9375] unweighted_recall 0.7457386363636364 [0.772727,0.71875] usercpu_time_millis 286.61399999998594 usercpu_time_millis 288.5699999999929 usercpu_time_millis 288.0260000000021 usercpu_time_millis 284.78199999995013 usercpu_time_millis 280.0039999999626 usercpu_time_millis 279.0780000000268 usercpu_time_millis 277.11800000002995 usercpu_time_millis 279.3839999999932 usercpu_time_millis 287.38399999997455 usercpu_time_millis 301.21400000001586 usercpu_time_millis_testing 11.140000000011696 usercpu_time_millis_testing 11.368000000004486 usercpu_time_millis_testing 11.0779999999977 usercpu_time_millis_testing 12.465999999960786 usercpu_time_millis_testing 12.107999999955155 usercpu_time_millis_testing 11.797999999998865 usercpu_time_millis_testing 10.632000000043718 usercpu_time_millis_testing 11.213999999995394 usercpu_time_millis_testing 11.002000000019052 usercpu_time_millis_testing 14.972000000000207 usercpu_time_millis_training 275.47399999997424 usercpu_time_millis_training 277.2019999999884 usercpu_time_millis_training 276.9480000000044 usercpu_time_millis_training 272.31599999998934 usercpu_time_millis_training 267.89600000000746 usercpu_time_millis_training 267.28000000002794 usercpu_time_millis_training 266.48599999998623 usercpu_time_millis_training 268.1699999999978 usercpu_time_millis_training 276.3819999999555 usercpu_time_millis_training 286.24200000001565 wall_clock_time_millis 145.27392387390137 wall_clock_time_millis 145.63775062561035 wall_clock_time_millis 146.21806144714355 wall_clock_time_millis 150.61116218566895 wall_clock_time_millis 141.035795211792 wall_clock_time_millis 140.31457901000977 wall_clock_time_millis 139.2369270324707 wall_clock_time_millis 140.3181552886963 wall_clock_time_millis 145.53499221801758 wall_clock_time_millis 151.5359878540039 wall_clock_time_millis_testing 5.587100982666016 wall_clock_time_millis_testing 5.699872970581055 wall_clock_time_millis_testing 5.689859390258789 wall_clock_time_millis_testing 6.365060806274414 wall_clock_time_millis_testing 6.247043609619141 wall_clock_time_millis_testing 5.963802337646484 wall_clock_time_millis_testing 5.321025848388672 wall_clock_time_millis_testing 5.685091018676758 wall_clock_time_millis_testing 5.529880523681641 wall_clock_time_millis_testing 7.513999938964844 wall_clock_time_millis_training 139.68682289123535 wall_clock_time_millis_training 139.9378776550293 wall_clock_time_millis_training 140.52820205688477 wall_clock_time_millis_training 144.24610137939453 wall_clock_time_millis_training 134.78875160217285 wall_clock_time_millis_training 134.35077667236328 wall_clock_time_millis_training 133.91590118408203 wall_clock_time_millis_training 134.63306427001953 wall_clock_time_millis_training 140.00511169433594 wall_clock_time_millis_training 144.02198791503906 weighted_recall 0.8888888888888888 [0.869565,0.903226] weighted_recall 0.8518518518518519 [0.869565,0.83871] weighted_recall 0.8148148148148148 [0.695652,0.903226] weighted_recall 0.7592592592592593 [0.652174,0.83871] weighted_recall 0.7777777777777778 [0.695652,0.83871] weighted_recall 0.7407407407407407 [0.608696,0.83871] weighted_recall 0.8703703703703703 [0.782609,0.935484] weighted_recall 0.8148148148148148 [0.695652,0.903226] weighted_recall 0.9074074074074074 [0.863636,0.9375] weighted_recall 0.7407407407407407 [0.772727,0.71875]