10397106 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) 8235638 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 131.79955149814975 13389 cache_size 200 13389 class_weight null 13389 coef0 0.0 13389 decision_function_shape "ovr" 13389 degree 3 13389 gamma 0.005449601498518041 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 21715955 description https://api.openml.org/data/download/21715955/description.xml -1 21715956 predictions https://api.openml.org/data/download/21715956/predictions.arff area_under_roc_curve 0.9563139754550584 [0.956314,0.956314] average_cost 0 f_measure 0.9643685639835278 [0.937621,0.975063] kappa 0.9126835963045465 kb_relative_information_score 0.9053289465028433 mean_absolute_error 0.03563034963005948 mean_prior_absolute_error 0.4080904194746198 number_of_instances 34465 [9844,24621] precision 0.9643674854234295 [0.937716,0.975023] predictive_accuracy 0.9643696503699405 prior_entropy 0.8629999933345911 recall 0.9643696503699405 [0.937525,0.975103] relative_absolute_error 0.08730993899815241 root_mean_prior_squared_error 0.4517106852187937 root_mean_squared_error 0.18876003186601628 root_relative_squared_error 0.417878164149664 total_cost 0 area_under_roc_curve 0.9566220304407672 [0.956622,0.956622] area_under_roc_curve 0.956342497329974 [0.956342,0.956342] area_under_roc_curve 0.9587789218455549 [0.958779,0.958779] area_under_roc_curve 0.9554287092743715 [0.955429,0.955429] area_under_roc_curve 0.954820067049611 [0.95482,0.95482] area_under_roc_curve 0.9535661568029166 [0.953566,0.953566] area_under_roc_curve 0.9565154577215959 [0.956515,0.956515] area_under_roc_curve 0.9615951074214235 [0.961595,0.961595] area_under_roc_curve 0.9577331536922193 [0.957733,0.957733] area_under_roc_curve 0.9517358978423253 [0.951736,0.951736] 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 0.9637750444286938 [0.936709,0.974588] f_measure 0.9637640553163636 [0.936709,0.974588] f_measure 0.9646813207991943 [0.938508,0.975153] f_measure 0.9628999859191382 [0.935223,0.973973] f_measure 0.9645414700751223 [0.937692,0.975284] f_measure 0.9636532131760568 [0.936061,0.974681] f_measure 0.9632068433586349 [0.935826,0.97415] f_measure 0.9678228953187247 [0.943797,0.977425] f_measure 0.9657469338888912 [0.93998,0.976045] f_measure 0.9635843155938562 [0.935666,0.974742] kappa 0.9112976391121674 kappa 0.9112974199823985 kappa 0.9136625511361747 kappa 0.9091961682666522 kappa 0.912976449047433 kappa 0.9107439242669191 kappa 0.9099775088789944 kappa 0.9212231251500856 kappa 0.9160251618046119 kappa 0.9104146900358674 kb_relative_information_score 0.9036236064366986 kb_relative_information_score 0.9036664436327781 kb_relative_information_score 0.9059784489855902 kb_relative_information_score 0.9013544382799646 kb_relative_information_score 0.9059784489855914 kb_relative_information_score 0.903607878355809 kb_relative_information_score 0.9020656044095022 kb_relative_information_score 0.9144037959799591 kb_relative_information_score 0.9090058371678841 kb_relative_information_score 0.9036078783558094 mean_absolute_error 0.03626341746446185 mean_absolute_error 0.03626341746446185 mean_absolute_error 0.035393095445314764 mean_absolute_error 0.03713373948360894 mean_absolute_error 0.035393095445314764 mean_absolute_error 0.03627394080092861 mean_absolute_error 0.03685432385374347 mean_absolute_error 0.03221125943122461 mean_absolute_error 0.03424260011607661 mean_absolute_error 0.03627394080092861 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 0.9638230450109476 [0.933401,0.975977] precision 0.9637963976519242 [0.934343,0.97558] precision 0.9647937712281813 [0.931932,0.977941] precision 0.9629407101991346 [0.932392,0.975163] precision 0.9645043995644184 [0.943474,0.972918] precision 0.9636136627129871 [0.942327,0.972121] precision 0.9632915009149062 [0.930653,0.976336] precision 0.9678666517462877 [0.940464,0.978819] precision 0.9657372533446863 [0.940937,0.975649] precision 0.9635665929487941 [0.947862,0.969843] predictive_accuracy 0.9637365825355382 predictive_accuracy 0.9637365825355382 predictive_accuracy 0.9646069045546852 predictive_accuracy 0.962866260516391 predictive_accuracy 0.9646069045546852 predictive_accuracy 0.9637260591990714 predictive_accuracy 0.9631456761462566 predictive_accuracy 0.9677887405687754 predictive_accuracy 0.9657573998839234 predictive_accuracy 0.9637260591990714 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 0.9637365825355382 [0.940041,0.973203] recall 0.9637365825355382 [0.939086,0.973599] recall 0.9646069045546852 [0.945178,0.97238] recall 0.962866260516391 [0.938071,0.972786] recall 0.9646069045546852 [0.93198,0.97766] recall 0.9637260591990714 [0.929878,0.977254] recall 0.9631456761462566 [0.941057,0.971974] recall 0.9677887405687754 [0.947154,0.976036] recall 0.9657573998839234 [0.939024,0.976442] recall 0.9637260591990714 [0.92378,0.979691] relative_absolute_error 0.0888759354754974 relative_absolute_error 0.0888488517264822 relative_absolute_error 0.08671647928504661 relative_absolute_error 0.09098122416791778 relative_absolute_error 0.08671647928504661 relative_absolute_error 0.08889398886709918 relative_absolute_error 0.09031629268897276 relative_absolute_error 0.07893786211398407 relative_absolute_error 0.08391592549054164 relative_absolute_error 0.08889398886709918 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 0.19042956037459585 root_mean_squared_error 0.19042956037459585 root_mean_squared_error 0.18813052768042396 root_mean_squared_error 0.19270116627464645 root_mean_squared_error 0.18813052768042396 root_mean_squared_error 0.1904571888927499 root_mean_squared_error 0.19197480004871337 root_mean_squared_error 0.17947495488570156 root_mean_squared_error 0.18504756176744563 root_mean_squared_error 0.1904571888927499 root_relative_squared_error 0.42164393946361445 root_relative_squared_error 0.4215154457713053 root_relative_squared_error 0.41642654156430936 root_relative_squared_error 0.42654364082512475 root_relative_squared_error 0.41642654156430936 root_relative_squared_error 0.4216684052877428 root_relative_squared_error 0.425028366020663 root_relative_squared_error 0.39735395894328573 root_relative_squared_error 0.4096915990753353 root_relative_squared_error 0.4216684052877428 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 88337.213134997 usercpu_time_millis 85405.36621000501 usercpu_time_millis 82290.20834200492 usercpu_time_millis 85044.32399699726 usercpu_time_millis 87679.77031999908 usercpu_time_millis 81790.43247800291 usercpu_time_millis 89492.84274299862 usercpu_time_millis 88647.872619993 usercpu_time_millis 88494.43984101526 usercpu_time_millis 83063.72746599664 usercpu_time_millis_testing 4170.3418649995 usercpu_time_millis_testing 4163.067024004704 usercpu_time_millis_testing 3132.2212150043924 usercpu_time_millis_testing 4144.519315996149 usercpu_time_millis_testing 4215.574663998268 usercpu_time_millis_testing 2832.5414920036565 usercpu_time_millis_testing 4178.80562999926 usercpu_time_millis_testing 4130.352423002478 usercpu_time_millis_testing 4217.82443500706 usercpu_time_millis_testing 3705.818090995308 usercpu_time_millis_training 84166.8712699975 usercpu_time_millis_training 81242.29918600031 usercpu_time_millis_training 79157.98712700052 usercpu_time_millis_training 80899.80468100111 usercpu_time_millis_training 83464.19565600081 usercpu_time_millis_training 78957.89098599926 usercpu_time_millis_training 85314.03711299936 usercpu_time_millis_training 84517.52019699052 usercpu_time_millis_training 84276.6154060082 usercpu_time_millis_training 79357.90937500133 wall_clock_time_millis 88338.00721168518 wall_clock_time_millis 85412.26148605347 wall_clock_time_millis 82297.68538475037 wall_clock_time_millis 85048.47121238708 wall_clock_time_millis 87684.47613716125 wall_clock_time_millis 81791.179895401 wall_clock_time_millis 89496.39630317688 wall_clock_time_millis 88649.40214157104 wall_clock_time_millis 88495.19944190979 wall_clock_time_millis 83068.96471977234 wall_clock_time_millis_testing 4170.380592346191 wall_clock_time_millis_testing 4163.1059646606445 wall_clock_time_millis_testing 3132.251262664795 wall_clock_time_millis_testing 4144.555568695068 wall_clock_time_millis_testing 4215.610027313232 wall_clock_time_millis_testing 2832.5674533843994 wall_clock_time_millis_testing 4178.845167160034 wall_clock_time_millis_testing 4130.395412445068 wall_clock_time_millis_testing 4217.864751815796 wall_clock_time_millis_testing 3705.8632373809814 wall_clock_time_millis_training 84167.62661933899 wall_clock_time_millis_training 81249.15552139282 wall_clock_time_millis_training 79165.43412208557 wall_clock_time_millis_training 80903.91564369202 wall_clock_time_millis_training 83468.86610984802 wall_clock_time_millis_training 78958.6124420166 wall_clock_time_millis_training 85317.55113601685 wall_clock_time_millis_training 84519.00672912598 wall_clock_time_millis_training 84277.334690094 wall_clock_time_millis_training 79363.10148239136