10396174 8323 Heinrich Peters 9977 Supervised Classification 16374 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)(2) 8235392 add_indicator false 12737 copy true 12737 fill_value null 12737 missing_values NaN 12737 strategy "most_frequent" 12737 verbose 0 12737 copy true 13294 with_mean true 13294 with_std true 13294 C 23.39518166892507 13389 cache_size 200 13389 class_weight null 13389 coef0 0.0 13389 decision_function_shape "ovr" 13389 degree 3 13389 gamma 0.024373975544459605 13389 kernel "rbf" 13389 max_iter -1 13389 probability false 13389 random_state 1 13389 shrinking true 13389 tol 0.001 13389 verbose false 13389 categorical_features null 16348 categories null 16348 drop null 16348 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 16348 handle_unknown "ignore" 16348 n_values null 16348 sparse true 16348 memory null 16374 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"}}] 16374 verbose false 16374 n_jobs null 16375 remainder "drop" 16375 sparse_threshold 0.3 16375 transformer_weights null 16375 transformers [{"oml-python:serialized_object": "component_reference", "value": {"key": "num", "step_name": "num", "argument_1": [true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, false, true, true, true, false, true, true, true, false, true, true, true, false, true, true, true, false, true, true, true, false, true, true, true, false, true, true]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "cat", "step_name": "cat", "argument_1": [false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, true, false, false, false, true, false, false, false, true, false, false, false, true, false, false, false, true, false, false, false, true, false, false, false, true, false, false]}}] 16375 verbose false 16375 memory null 16376 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}] 16376 verbose false 16376 memory null 16377 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}] 16377 verbose false 16377 openml-python Sklearn_0.21.2. 1486 nomao https://www.openml.org/data/download/1592278/phpDYCOet -1 21714080 description https://api.openml.org/data/download/21714080/description.xml -1 21714081 predictions https://api.openml.org/data/download/21714081/predictions.arff area_under_roc_curve 0.954302407347893 [0.954302,0.954302] average_cost 0 f_measure 0.9635465645350735 [0.936025,0.97455] kappa 0.9105756637909301 kb_relative_information_score 0.9032474168249748 mean_absolute_error 0.03641375308283766 mean_prior_absolute_error 0.4080904194746198 number_of_instances 34465 [9844,24621] precision 0.9635167729035062 [0.939425,0.973149] predictive_accuracy 0.9635862469171623 prior_entropy 0.8629999933345911 recall 0.9635862469171623 [0.932649,0.975955] relative_absolute_error 0.08922962006733001 root_mean_prior_squared_error 0.4517106852187937 root_mean_squared_error 0.19082387974998744 root_relative_squared_error 0.42244712377693405 total_cost 0 area_under_roc_curve 0.956620792608657 [0.956621,0.956621] area_under_roc_curve 0.9570531984643742 [0.957053,0.957053] area_under_roc_curve 0.9497433063787849 [0.949743,0.949743] area_under_roc_curve 0.9569519642731964 [0.956952,0.956952] area_under_roc_curve 0.9520789090624188 [0.952079,0.952079] area_under_roc_curve 0.953362244325124 [0.953362,0.953362] area_under_roc_curve 0.955397241320098 [0.955397,0.955397] area_under_roc_curve 0.9564118503695191 [0.956412,0.956412] area_under_roc_curve 0.9570219366897162 [0.957022,0.957022] area_under_roc_curve 0.9483820741944218 [0.948382,0.948382] 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 0.9646069045546852 [0.938008,0.975233] f_measure 0.9643438304313017 [0.937722,0.974995] f_measure 0.9590886306189923 [0.92839,0.971371] f_measure 0.9654508144993634 [0.93944,0.975857] f_measure 0.9627743644401617 [0.934493,0.974089] f_measure 0.964201061136724 [0.936891,0.975116] f_measure 0.9628892769456888 [0.935157,0.973973] f_measure 0.9651449611357635 [0.938838,0.975659] f_measure 0.9651663734463302 [0.938962,0.975639] f_measure 0.961787288382674 [0.9323,0.973573] kappa 0.9132415852173138 kappa 0.9127166612626801 kappa 0.8997606144209238 kappa 0.9152975940348004 kappa 0.9085848402198855 kappa 0.9120103364365616 kappa 0.9091305383260777 kappa 0.9144974679241445 kappa 0.9146018594623173 kappa 0.9058831525534969 kb_relative_information_score 0.9059366398822177 kb_relative_information_score 0.9052077805346538 kb_relative_information_score 0.8913357484177724 kb_relative_information_score 0.908290454338405 kb_relative_information_score 0.9013544382799645 kb_relative_information_score 0.9051501523021159 kb_relative_information_score 0.9012944674363488 kb_relative_information_score 0.9074635632215774 kb_relative_information_score 0.9074635632215768 kb_relative_information_score 0.898981056516888 mean_absolute_error 0.035393095445314764 mean_absolute_error 0.03568320278503046 mean_absolute_error 0.040905134899912966 mean_absolute_error 0.034522773426167684 mean_absolute_error 0.03713373948360894 mean_absolute_error 0.03569355774811375 mean_absolute_error 0.0371445153801509 mean_absolute_error 0.034822983168891465 mean_absolute_error 0.034822983168891465 mean_absolute_error 0.03801508995937319 mean_prior_absolute_error 0.4080229059806574 mean_prior_absolute_error 0.4081472833897437 mean_prior_absolute_error 0.4081472833897437 mean_prior_absolute_error 0.4081472833897437 mean_prior_absolute_error 0.4081472833897437 mean_prior_absolute_error 0.40805842175852763 mean_prior_absolute_error 0.40805842175852763 mean_prior_absolute_error 0.40805842175852763 mean_prior_absolute_error 0.40805842175852763 mean_prior_absolute_error 0.40805842175852763 number_of_instances 3447 [984,2463] number_of_instances 3447 [985,2462] number_of_instances 3447 [985,2462] number_of_instances 3447 [985,2462] number_of_instances 3447 [985,2462] number_of_instances 3446 [984,2462] number_of_instances 3446 [984,2462] number_of_instances 3446 [984,2462] number_of_instances 3446 [984,2462] number_of_instances 3446 [984,2462] precision 0.9646069045546852 [0.938008,0.975233] precision 0.9643757375117978 [0.935354,0.975987] precision 0.9590825902009874 [0.928862,0.971173] precision 0.9654293131326488 [0.941837,0.974868] precision 0.9627328768315867 [0.942208,0.970944] precision 0.9641671207687434 [0.946114,0.971383] precision 0.9629300748127563 [0.932323,0.975163] precision 0.9651199846785475 [0.941718,0.974473] precision 0.9651565148155028 [0.939919,0.975244] precision 0.9618062256763968 [0.948475,0.967134] predictive_accuracy 0.9646069045546852 predictive_accuracy 0.9643167972149694 predictive_accuracy 0.959094865100087 predictive_accuracy 0.9654772265738323 predictive_accuracy 0.962866260516391 predictive_accuracy 0.9643064422518863 predictive_accuracy 0.9628554846198492 predictive_accuracy 0.9651770168311086 predictive_accuracy 0.9651770168311086 predictive_accuracy 0.9619849100406267 prior_entropy 0.862791736866817 prior_entropy 0.863175399426382 prior_entropy 0.863175399426382 prior_entropy 0.863175399426382 prior_entropy 0.863175399426382 prior_entropy 0.862901291120622 prior_entropy 0.862901291120622 prior_entropy 0.862901291120622 prior_entropy 0.862901291120622 prior_entropy 0.862901291120622 recall 0.9646069045546852 [0.938008,0.975233] recall 0.9643167972149695 [0.940102,0.974005] recall 0.959094865100087 [0.927919,0.971568] recall 0.9654772265738323 [0.937056,0.976848] recall 0.962866260516391 [0.926904,0.977254] recall 0.9643064422518862 [0.927846,0.978879] recall 0.9628554846198492 [0.938008,0.972786] recall 0.9651770168311086 [0.935976,0.976848] recall 0.9651770168311086 [0.938008,0.976036] recall 0.9619849100406268 [0.916667,0.980097] relative_absolute_error 0.08674291302408546 relative_absolute_error 0.08742727009885849 relative_absolute_error 0.10022150474747192 relative_absolute_error 0.08458410684361105 relative_absolute_error 0.09098122416791778 relative_absolute_error 0.08747168504522557 relative_absolute_error 0.09102744459990955 relative_absolute_error 0.0853382293124152 relative_absolute_error 0.0853382293124152 relative_absolute_error 0.09316090033271993 root_mean_prior_squared_error 0.4516359481339797 root_mean_prior_squared_error 0.45177362368332785 root_mean_prior_squared_error 0.45177362368332785 root_mean_prior_squared_error 0.45177362368332785 root_mean_prior_squared_error 0.45177362368332785 root_mean_prior_squared_error 0.4516752654560011 root_mean_prior_squared_error 0.4516752654560011 root_mean_prior_squared_error 0.4516752654560011 root_mean_prior_squared_error 0.4516752654560011 root_mean_prior_squared_error 0.4516752654560011 root_mean_squared_error 0.18813052768042396 root_mean_squared_error 0.18889998090267363 root_mean_squared_error 0.20225017898610861 root_mean_squared_error 0.185803050099205 root_mean_squared_error 0.19270116627464645 root_mean_squared_error 0.1889273875014254 root_mean_squared_error 0.19272912436928388 root_mean_squared_error 0.18660917225284362 root_mean_squared_error 0.18660917225284362 root_mean_squared_error 0.19497458798359643 root_relative_squared_error 0.4165534839680526 root_relative_squared_error 0.4181297247116039 root_relative_squared_error 0.4476803611002233 root_relative_squared_error 0.41127467465750994 root_relative_squared_error 0.42654364082512475 root_relative_squared_error 0.41828145561765173 root_relative_squared_error 0.4266984249728816 root_relative_squared_error 0.4131489734432263 root_relative_squared_error 0.4131489734432263 root_relative_squared_error 0.4316698364847463 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 usercpu_time_millis 198493.53643700306 usercpu_time_millis 184615.40522999712 usercpu_time_millis 182632.33451999986 usercpu_time_millis 190759.281096005 usercpu_time_millis 190152.54456600087 usercpu_time_millis 257956.3865050004 usercpu_time_millis 171309.6426159973 usercpu_time_millis 197798.75447099766 usercpu_time_millis 160528.49247500126 usercpu_time_millis 189363.51230100263 usercpu_time_millis_testing 6439.228376002575 usercpu_time_millis_testing 6196.897073998116 usercpu_time_millis_testing 6120.569143000466 usercpu_time_millis_testing 6371.763680006552 usercpu_time_millis_testing 6439.465994000784 usercpu_time_millis_testing 6450.0565429989365 usercpu_time_millis_testing 4445.381840996561 usercpu_time_millis_testing 6555.425054000807 usercpu_time_millis_testing 4408.299511000223 usercpu_time_millis_testing 6361.924582000938 usercpu_time_millis_training 192054.30806100048 usercpu_time_millis_training 178418.508155999 usercpu_time_millis_training 176511.7653769994 usercpu_time_millis_training 184387.51741599845 usercpu_time_millis_training 183713.0785720001 usercpu_time_millis_training 251506.32996200147 usercpu_time_millis_training 166864.26077500073 usercpu_time_millis_training 191243.32941699686 usercpu_time_millis_training 156120.19296400103 usercpu_time_millis_training 183001.5877190017 wall_clock_time_millis 198499.00031089783 wall_clock_time_millis 184621.19317054749 wall_clock_time_millis 182633.82077217102 wall_clock_time_millis 190760.61820983887 wall_clock_time_millis 190153.69606018066 wall_clock_time_millis 257959.29169654846 wall_clock_time_millis 171310.3814125061 wall_clock_time_millis 197912.0922088623 wall_clock_time_millis 160529.37841415405 wall_clock_time_millis 189365.53359031677 wall_clock_time_millis_testing 6439.33892250061 wall_clock_time_millis_testing 6196.955442428589 wall_clock_time_millis_testing 6120.619058609009 wall_clock_time_millis_testing 6371.818780899048 wall_clock_time_millis_testing 6439.532041549683 wall_clock_time_millis_testing 6450.108528137207 wall_clock_time_millis_testing 4445.415019989014 wall_clock_time_millis_testing 6559.552907943726 wall_clock_time_millis_testing 4408.337354660034 wall_clock_time_millis_testing 6362.028121948242 wall_clock_time_millis_training 192059.66138839722 wall_clock_time_millis_training 178424.2377281189 wall_clock_time_millis_training 176513.201713562 wall_clock_time_millis_training 184388.79942893982 wall_clock_time_millis_training 183714.16401863098 wall_clock_time_millis_training 251509.18316841125 wall_clock_time_millis_training 166864.9663925171 wall_clock_time_millis_training 191352.53930091858 wall_clock_time_millis_training 156121.04105949402 wall_clock_time_millis_training 183003.50546836853