10554602 8323 Heinrich Peters 9977 Supervised Classification 18607 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)),logisticregression=sklearn.linear_model.logistic.LogisticRegression)(2) 8275814 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 500 17462 class_weight null 17462 dual false 17462 fit_intercept true 17462 intercept_scaling 1 17462 l1_ratio null 17462 max_iter 100 17462 multi_class "warn" 17462 n_jobs null 17462 penalty "l2" 17462 random_state 1 17462 solver "lbfgs" 17462 tol 0.0001 17462 verbose 0 17462 warm_start false 17462 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": [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]}}] 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 memory null 18607 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": "logisticregression", "step_name": "logisticregression"}}] 18607 verbose false 18607 openml-python Sklearn_0.21.2. 1486 nomao https://www.openml.org/data/download/1592278/phpDYCOet -1 22034159 description https://api.openml.org/data/download/22034159/description.xml -1 22034160 predictions https://api.openml.org/data/download/22034160/predictions.arff area_under_roc_curve 0.9880219685078369 [0.988022,0.988022] average_cost 0 f_measure 0.9490436684539222 [0.910538,0.964439] kappa 0.8749776780605797 kb_relative_information_score 0.8246115215383314 mean_absolute_error 0.07245678777998737 mean_prior_absolute_error 0.4080904194746198 weighted_recall 0.9491077905121137 [0.906745,0.966045] number_of_instances 34465 [9844,24621] precision 0.9489924534959034 [0.914362,0.962839] predictive_accuracy 0.9491077905121138 prior_entropy 0.8629999933345911 relative_absolute_error 0.1775508179615416 root_mean_prior_squared_error 0.4517106852187937 root_mean_squared_error 0.1918626925275774 root_relative_squared_error 0.4247468541388288 total_cost 0 unweighted_recall 0.9363952357231773 [0.906745,0.966045] area_under_roc_curve 0.9876930605481452 [0.987693,0.987693] area_under_roc_curve 0.9874993299162499 [0.987499,0.987499] area_under_roc_curve 0.9865719340060286 [0.986572,0.986572] area_under_roc_curve 0.9883388933102962 [0.988339,0.988339] area_under_roc_curve 0.988370644971073 [0.988371,0.988371] area_under_roc_curve 0.9887129902980589 [0.988713,0.988713] area_under_roc_curve 0.9874891026530086 [0.987489,0.987489] area_under_roc_curve 0.9908478796404536 [0.990848,0.990848] area_under_roc_curve 0.9880352083374613 [0.988035,0.988035] area_under_roc_curve 0.9869248347235707 [0.986925,0.986925] 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 0.948909826958246 [0.910387,0.9643] f_measure 0.9495059205520612 [0.911585,0.964677] f_measure 0.9452112516383417 [0.904304,0.961578] f_measure 0.9515446901657569 [0.915185,0.966091] f_measure 0.947514486797487 [0.908262,0.963219] f_measure 0.9472532354868543 [0.906749,0.963442] f_measure 0.9484699951788093 [0.910282,0.963733] f_measure 0.9531999287118477 [0.917731,0.967376] f_measure 0.9520072304816823 [0.915515,0.966592] f_measure 0.9467975373984112 [0.905307,0.96338] kappa 0.8746873752909362 kappa 0.8762626398079216 kappa 0.8658816990133863 kappa 0.8812767560871936 kappa 0.8714805077523843 kappa 0.8702006738379002 kappa 0.8740182514853567 kappa 0.8851085472269588 kappa 0.882109770464557 kappa 0.8687163350796739 kb_relative_information_score 0.8216547359169796 kb_relative_information_score 0.8251539919338591 kb_relative_information_score 0.8142169683637762 kb_relative_information_score 0.8231213767087092 kb_relative_information_score 0.8226289077133832 kb_relative_information_score 0.8232786782681386 kb_relative_information_score 0.8235973635877812 kb_relative_information_score 0.8381700010900766 kb_relative_information_score 0.8328277541907765 kb_relative_information_score 0.8214740208791443 mean_absolute_error 0.07367968399558442 mean_absolute_error 0.07274478995718749 mean_absolute_error 0.07651151862436656 mean_absolute_error 0.0730601905978451 mean_absolute_error 0.07311372137775415 mean_absolute_error 0.07287164223235226 mean_absolute_error 0.07234299571111014 mean_absolute_error 0.06709563371163446 mean_absolute_error 0.06921662010609342 mean_absolute_error 0.07392910064855228 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 0.9488816088825129 [0.912245,0.963518] precision 0.949491283435967 [0.912513,0.964286] precision 0.9452575221359673 [0.90202,0.962556] precision 0.9515374978696863 [0.91565,0.965895] precision 0.9475401135778501 [0.906883,0.963806] precision 0.9471723012559924 [0.91954,0.958216] precision 0.9486425291223688 [0.903,0.966885] precision 0.9531441202044038 [0.922919,0.965224] precision 0.9519396469581897 [0.922601,0.963666] precision 0.946824188709654 [0.927505,0.954545] predictive_accuracy 0.9489411082100377 predictive_accuracy 0.9495213228894691 predictive_accuracy 0.9451697127937336 predictive_accuracy 0.9515520742674789 predictive_accuracy 0.9474905715114592 predictive_accuracy 0.9474753337202554 predictive_accuracy 0.9483459082994777 predictive_accuracy 0.953279164248404 predictive_accuracy 0.9521183981427742 predictive_accuracy 0.947185142193848 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 relative_absolute_error 0.18057732278167063 relative_absolute_error 0.17823171418177197 relative_absolute_error 0.18746056077826442 relative_absolute_error 0.1790044760094097 relative_absolute_error 0.1791356315556734 relative_absolute_error 0.17858139508140025 relative_absolute_error 0.17728587832925494 relative_absolute_error 0.16442653829440854 relative_absolute_error 0.1696242900901406 relative_absolute_error 0.18117283385539462 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 0.1928950304988265 root_mean_squared_error 0.19243704775697792 root_mean_squared_error 0.19995067924695728 root_mean_squared_error 0.1913992483580762 root_mean_squared_error 0.19539793222150428 root_mean_squared_error 0.1895628952186954 root_mean_squared_error 0.1929011875033413 root_mean_squared_error 0.18215543769771786 root_mean_squared_error 0.18513451377397777 root_mean_squared_error 0.1961538264946312 root_relative_squared_error 0.427102916177973 root_relative_squared_error 0.4259590150217962 root_relative_squared_error 0.4425904230901124 root_relative_squared_error 0.4236618481565849 root_relative_squared_error 0.432512926780491 root_relative_squared_error 0.4196884569876037 root_relative_squared_error 0.4270793693088166 root_relative_squared_error 0.40328849425442376 root_relative_squared_error 0.40988410907794603 root_relative_squared_error 0.43428064695240454 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 0.9368099085984769 [0.908537,0.965083] unweighted_recall 0.9378644740151831 [0.91066,0.965069] unweighted_recall 0.9336000610291662 [0.906599,0.960601] unweighted_recall 0.9405041916315817 [0.914721,0.966288] unweighted_recall 0.9361383382747714 [0.909645,0.962632] unweighted_recall 0.9315167786121403 [0.894309,0.968725] unweighted_recall 0.9391420320580135 [0.917683,0.960601] unweighted_recall 0.9410692939179595 [0.912602,0.969537] unweighted_recall 0.9390367735927563 [0.908537,0.969537] unweighted_recall 0.9282632600899526 [0.884146,0.97238] usercpu_time_millis 2807.9859999998007 usercpu_time_millis 2754.088000001502 usercpu_time_millis 2746.2480000031064 usercpu_time_millis 2700.5040000003646 usercpu_time_millis 2803.6600000050385 usercpu_time_millis 2676.1760000081267 usercpu_time_millis 2709.7280000016326 usercpu_time_millis 2618.0659999954514 usercpu_time_millis 2661.5339999989374 usercpu_time_millis 2682.224000003771 usercpu_time_millis_testing 79.41399999981513 usercpu_time_millis_testing 78.98199999908684 usercpu_time_millis_testing 87.19600000040373 usercpu_time_millis_testing 85.60600000055274 usercpu_time_millis_testing 84.83400000113761 usercpu_time_millis_testing 81.6700000068522 usercpu_time_millis_testing 77.76600000215694 usercpu_time_millis_testing 78.66799999465002 usercpu_time_millis_testing 81.95200000045588 usercpu_time_millis_testing 78.70200000616023 usercpu_time_millis_training 2728.5719999999856 usercpu_time_millis_training 2675.1060000024154 usercpu_time_millis_training 2659.0520000027027 usercpu_time_millis_training 2614.897999999812 usercpu_time_millis_training 2718.826000003901 usercpu_time_millis_training 2594.5060000012745 usercpu_time_millis_training 2631.9619999994757 usercpu_time_millis_training 2539.3980000008014 usercpu_time_millis_training 2579.5819999984815 usercpu_time_millis_training 2603.5219999976107 wall_clock_time_millis 969.5792198181152 wall_clock_time_millis 943.1142807006836 wall_clock_time_millis 959.758996963501 wall_clock_time_millis 935.8100891113281 wall_clock_time_millis 964.86496925354 wall_clock_time_millis 941.6060447692871 wall_clock_time_millis 933.4170818328857 wall_clock_time_millis 919.5928573608398 wall_clock_time_millis 907.5686931610107 wall_clock_time_millis 925.102949142456 wall_clock_time_millis_testing 27.929067611694336 wall_clock_time_millis_testing 25.83909034729004 wall_clock_time_millis_testing 30.07984161376953 wall_clock_time_millis_testing 29.60515022277832 wall_clock_time_millis_testing 27.186870574951172 wall_clock_time_millis_testing 27.736902236938477 wall_clock_time_millis_testing 31.41617774963379 wall_clock_time_millis_testing 25.339841842651367 wall_clock_time_millis_testing 27.861833572387695 wall_clock_time_millis_testing 24.283170700073242 wall_clock_time_millis_training 941.6501522064209 wall_clock_time_millis_training 917.2751903533936 wall_clock_time_millis_training 929.6791553497314 wall_clock_time_millis_training 906.2049388885498 wall_clock_time_millis_training 937.6780986785889 wall_clock_time_millis_training 913.8691425323486 wall_clock_time_millis_training 902.000904083252 wall_clock_time_millis_training 894.2530155181885 wall_clock_time_millis_training 879.706859588623 wall_clock_time_millis_training 900.8197784423828 weighted_recall 0.9489411082100377 [0.908537,0.965083] weighted_recall 0.9495213228894691 [0.91066,0.965069] weighted_recall 0.9451697127937336 [0.906599,0.960601] weighted_recall 0.951552074267479 [0.914721,0.966288] weighted_recall 0.9474905715114592 [0.909645,0.962632] weighted_recall 0.9474753337202554 [0.894309,0.968725] weighted_recall 0.9483459082994776 [0.917683,0.960601] weighted_recall 0.953279164248404 [0.912602,0.969537] weighted_recall 0.9521183981427742 [0.908537,0.969537] weighted_recall 0.947185142193848 [0.884146,0.97238]