10558897 8323 Heinrich Peters 125920 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) 8275996 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 0.1 17462 class_weight null 17462 dual false 17462 fit_intercept true 17462 intercept_scaling 1 17462 l1_ratio null 17462 max_iter 10000 17462 multi_class "auto" 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": [false, false, true, false, false, false, false, false, false, false, false, false]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "cat", "step_name": "cat", "argument_1": [true, true, false, true, true, true, true, true, true, true, true, 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 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. 23381 dresses-sales https://www.openml.org/data/download/1910507/phpcFPMhq -1 22042758 description https://api.openml.org/data/download/22042758/description.xml -1 22042759 predictions https://api.openml.org/data/download/22042759/predictions.arff area_under_roc_curve 0.654712643678161 [0.654713,0.654713] average_cost 0 f_measure 0.6135418900938505 [0.722307,0.463343] kappa 0.2076550051957049 kb_relative_information_score 0.08551851860045032 mean_absolute_error 0.4517034079025114 mean_prior_absolute_error 0.4872509960159361 weighted_recall 0.634 [0.82069,0.37619] number_of_instances 500 [290,210] precision 0.6273745836695008 [0.644986,0.603053] predictive_accuracy 0.634 prior_entropy 0.9814541958069474 relative_absolute_error 0.9270446065701585 root_mean_prior_squared_error 0.4935586100816085 root_mean_squared_error 0.47636297406634914 root_relative_squared_error 0.9651598905094247 total_cost 0 unweighted_recall 0.598440065681445 [0.82069,0.37619] area_under_roc_curve 0.6059113300492611 [0.605911,0.605911] area_under_roc_curve 0.7159277504105092 [0.715928,0.715928] area_under_roc_curve 0.6486042692939245 [0.648604,0.648604] area_under_roc_curve 0.573070607553366 [0.573071,0.573071] area_under_roc_curve 0.6551724137931035 [0.655172,0.655172] area_under_roc_curve 0.6995073891625617 [0.699507,0.699507] area_under_roc_curve 0.6847290640394089 [0.684729,0.684729] area_under_roc_curve 0.7602627257799671 [0.760263,0.760263] area_under_roc_curve 0.5238095238095238 [0.52381,0.52381] area_under_roc_curve 0.6880131362889983 [0.688013,0.688013] 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 0.6024615384615384 [0.707692,0.457143] f_measure 0.728 [0.8,0.628571] f_measure 0.49277777777777787 [0.694444,0.214286] f_measure 0.5771836007130124 [0.69697,0.411765] f_measure 0.5771836007130124 [0.69697,0.411765] f_measure 0.636472184531886 [0.746269,0.484848] f_measure 0.6706872370266478 [0.782609,0.516129] f_measure 0.6773333333333333 [0.733333,0.6] f_measure 0.5187692307692308 [0.646154,0.342857] f_measure 0.626875 [0.71875,0.5] kappa 0.18244406196213422 kappa 0.44061962134251287 kappa 0.005424954792043555 kappa 0.1334488734835355 kappa 0.1334488734835355 kappa 0.25828970331588147 kappa 0.3362831858407078 kappa 0.33444259567387696 kappa 0.010327022375215203 kappa 0.23076923076923075 kb_relative_information_score 0.07464048567379286 kb_relative_information_score 0.14652471800690692 kb_relative_information_score 0.07244079414232346 kb_relative_information_score 0.05267708977482838 kb_relative_information_score 0.09883321472706198 kb_relative_information_score 0.08418575007202238 kb_relative_information_score 0.09150807378405994 kb_relative_information_score 0.16098237475077212 kb_relative_information_score -0.006644848821835128 kb_relative_information_score 0.08003753389456797 mean_absolute_error 0.4577410862938413 mean_absolute_error 0.4295430871125894 mean_absolute_error 0.4556902089353328 mean_absolute_error 0.46459350087214446 mean_absolute_error 0.44441309884013286 mean_absolute_error 0.4523691003425862 mean_absolute_error 0.4513094237577465 mean_absolute_error 0.41997259590242214 mean_absolute_error 0.48711397720495697 mean_absolute_error 0.45428799976336287 mean_prior_absolute_error 0.48725099601593624 mean_prior_absolute_error 0.48725099601593624 mean_prior_absolute_error 0.48725099601593624 mean_prior_absolute_error 0.48725099601593624 mean_prior_absolute_error 0.48725099601593624 mean_prior_absolute_error 0.48725099601593624 mean_prior_absolute_error 0.48725099601593624 mean_prior_absolute_error 0.48725099601593624 mean_prior_absolute_error 0.48725099601593624 mean_prior_absolute_error 0.48725099601593624 number_of_instances 50 [29,21] number_of_instances 50 [29,21] number_of_instances 50 [29,21] number_of_instances 50 [29,21] number_of_instances 50 [29,21] number_of_instances 50 [29,21] number_of_instances 50 [29,21] number_of_instances 50 [29,21] number_of_instances 50 [29,21] number_of_instances 50 [29,21] precision 0.6105555555555555 [0.638889,0.571429] precision 0.7488888888888888 [0.722222,0.785714] precision 0.5172093023255814 [0.581395,0.428571] precision 0.5866943866943867 [0.621622,0.538462] precision 0.5866943866943867 [0.621622,0.538462] precision 0.661578947368421 [0.657895,0.666667] precision 0.7275 [0.675,0.8] precision 0.6768760611205432 [0.709677,0.631579] precision 0.5183333333333333 [0.583333,0.428571] precision 0.6331428571428571 [0.657143,0.6] predictive_accuracy 0.62 predictive_accuracy 0.74 predictive_accuracy 0.56 predictive_accuracy 0.6 predictive_accuracy 0.6 predictive_accuracy 0.66 predictive_accuracy 0.7 predictive_accuracy 0.68 predictive_accuracy 0.54 predictive_accuracy 0.64 prior_entropy 0.9814541958069504 prior_entropy 0.9814541958069504 prior_entropy 0.9814541958069504 prior_entropy 0.9814541958069504 prior_entropy 0.9814541958069504 prior_entropy 0.9814541958069504 prior_entropy 0.9814541958069504 prior_entropy 0.9814541958069504 prior_entropy 0.9814541958069504 prior_entropy 0.9814541958069504 relative_absolute_error 0.939435917087115 relative_absolute_error 0.881564307974325 relative_absolute_error 0.9352268392703887 relative_absolute_error 0.9534993353958157 relative_absolute_error 0.912082484128155 relative_absolute_error 0.9284108273588646 relative_absolute_error 0.9262360209582533 relative_absolute_error 0.8619224985405394 relative_absolute_error 0.9997187921377285 relative_absolute_error 0.9323490428504013 root_mean_prior_squared_error 0.49355861008160823 root_mean_prior_squared_error 0.49355861008160823 root_mean_prior_squared_error 0.49355861008160823 root_mean_prior_squared_error 0.49355861008160823 root_mean_prior_squared_error 0.49355861008160823 root_mean_prior_squared_error 0.49355861008160823 root_mean_prior_squared_error 0.49355861008160823 root_mean_prior_squared_error 0.49355861008160823 root_mean_prior_squared_error 0.49355861008160823 root_mean_prior_squared_error 0.49355861008160823 root_mean_squared_error 0.4845822942530337 root_mean_squared_error 0.4574091025661922 root_mean_squared_error 0.4797677063208944 root_mean_squared_error 0.49152835886085466 root_mean_squared_error 0.47154302135732473 root_mean_squared_error 0.47931229428311994 root_mean_squared_error 0.4692285772466302 root_mean_squared_error 0.44817007427691424 root_mean_squared_error 0.5047167186139159 root_mean_squared_error 0.4749027567135817 root_relative_squared_error 0.9818130701294211 root_relative_squared_error 0.9267574168963665 root_relative_squared_error 0.9720582247396443 root_relative_squared_error 0.9958865042990176 root_relative_squared_error 0.9553941755354175 root_relative_squared_error 0.9711355135793646 root_relative_squared_error 0.9507048761018368 root_relative_squared_error 0.908038204830042 root_relative_squared_error 1.0226074640465956 root_relative_squared_error 0.9622013414679528 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 0.5870279146141215 [0.793103,0.380952] unweighted_recall 0.7101806239737274 [0.896552,0.52381] unweighted_recall 0.5024630541871921 [0.862069,0.142857] unweighted_recall 0.5632183908045977 [0.793103,0.333333] unweighted_recall 0.5632183908045977 [0.793103,0.333333] unweighted_recall 0.6215106732348111 [0.862069,0.380952] unweighted_recall 0.6559934318555007 [0.931034,0.380952] unweighted_recall 0.6650246305418719 [0.758621,0.571429] unweighted_recall 0.5049261083743842 [0.724138,0.285714] unweighted_recall 0.6108374384236454 [0.793103,0.428571] usercpu_time_millis 40.162000001146225 usercpu_time_millis 40.89200000089477 usercpu_time_millis 37.23399999944377 usercpu_time_millis 37.43000000031316 usercpu_time_millis 39.6599999985483 usercpu_time_millis 39.98200000205543 usercpu_time_millis 37.23600000012084 usercpu_time_millis 39.919999999256106 usercpu_time_millis 39.24800000095274 usercpu_time_millis 41.1260000000766 usercpu_time_millis_testing 8.608000000094762 usercpu_time_millis_testing 8.187999999790918 usercpu_time_millis_testing 5.185999998502666 usercpu_time_millis_testing 5.2500000019790605 usercpu_time_millis_testing 10.033999998995569 usercpu_time_millis_testing 6.3599999994039536 usercpu_time_millis_testing 6.313999998383224 usercpu_time_millis_testing 4.9360000011802185 usercpu_time_millis_testing 7.592000001750421 usercpu_time_millis_testing 8.003999999345979 usercpu_time_millis_training 31.554000001051463 usercpu_time_millis_training 32.70400000110385 usercpu_time_millis_training 32.0480000009411 usercpu_time_millis_training 32.1799999983341 usercpu_time_millis_training 29.625999999552732 usercpu_time_millis_training 33.622000002651475 usercpu_time_millis_training 30.922000001737615 usercpu_time_millis_training 34.98399999807589 usercpu_time_millis_training 31.655999999202322 usercpu_time_millis_training 33.12200000073062 wall_clock_time_millis 23.880720138549805 wall_clock_time_millis 21.39592170715332 wall_clock_time_millis 19.69599723815918 wall_clock_time_millis 19.37699317932129 wall_clock_time_millis 23.905038833618164 wall_clock_time_millis 23.95915985107422 wall_clock_time_millis 23.044347763061523 wall_clock_time_millis 29.706954956054688 wall_clock_time_millis 26.088953018188477 wall_clock_time_millis 21.913766860961914 wall_clock_time_millis_testing 5.0048828125 wall_clock_time_millis_testing 4.123926162719727 wall_clock_time_millis_testing 2.619028091430664 wall_clock_time_millis_testing 2.6388168334960938 wall_clock_time_millis_testing 7.992029190063477 wall_clock_time_millis_testing 3.1921863555908203 wall_clock_time_millis_testing 3.5390853881835938 wall_clock_time_millis_testing 2.4728775024414062 wall_clock_time_millis_testing 8.831977844238281 wall_clock_time_millis_testing 4.23884391784668 wall_clock_time_millis_training 18.875837326049805 wall_clock_time_millis_training 17.271995544433594 wall_clock_time_millis_training 17.076969146728516 wall_clock_time_millis_training 16.738176345825195 wall_clock_time_millis_training 15.913009643554688 wall_clock_time_millis_training 20.7669734954834 wall_clock_time_millis_training 19.50526237487793 wall_clock_time_millis_training 27.23407745361328 wall_clock_time_millis_training 17.256975173950195 wall_clock_time_millis_training 17.674922943115234 weighted_recall 0.62 [0.793103,0.380952] weighted_recall 0.74 [0.896552,0.52381] weighted_recall 0.56 [0.862069,0.142857] weighted_recall 0.6 [0.793103,0.333333] weighted_recall 0.6 [0.793103,0.333333] weighted_recall 0.66 [0.862069,0.380952] weighted_recall 0.7 [0.931034,0.380952] weighted_recall 0.68 [0.758621,0.571429] weighted_recall 0.54 [0.724138,0.285714] weighted_recall 0.64 [0.793103,0.428571]