10147852 1 Jan van Rijn 9976 Supervised Classification 8815 sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),variancethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,decisiontreeclassifier=sklearn.tree.tree.DecisionTreeClassifier)(1) 8073477 axis 0 8778 copy true 8778 missing_values "NaN" 8778 strategy "most_frequent" 8778 verbose 0 8778 copy true 8779 with_mean true 8779 with_std true 8779 memory null 8780 copy true 8781 fill_value -1 8781 missing_values NaN 8781 strategy "constant" 8781 verbose 0 8781 categorical_features null 8782 categories null 8782 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 8782 handle_unknown "ignore" 8782 n_values null 8782 sparse true 8782 class_weight null 8783 criterion "entropy" 8783 max_depth null 8783 max_features 1.0 8783 max_leaf_nodes null 8783 min_impurity_decrease 0.0 8783 min_impurity_split null 8783 min_samples_leaf 1 8783 min_samples_split 19 8783 min_weight_fraction_leaf 0.0 8783 presort false 8783 random_state 20772 8783 splitter "best" 8783 n_jobs null 8812 remainder "passthrough" 8812 sparse_threshold 0.3 8812 transformer_weights null 8812 memory null 8813 memory null 8815 threshold 0.0 8816 openml-python Sklearn_0.20.0. 1485 madelon https://www.openml.org/data/download/1590986/phpfLuQE4 -1 21216243 description https://api.openml.org/data/download/21216243/description.xml -1 21216244 predictions https://api.openml.org/data/download/21216244/predictions.arff area_under_roc_curve 0.8076781065088758 [0.807678,0.807678] average_cost 0 f_measure 0.7661526008126671 [0.765613,0.766692] kappa 0.5323076923076924 kb_relative_information_score 1390.4480927346244 mean_absolute_error 0.23289997489940942 mean_prior_absolute_error 0.5 number_of_instances 2600 [1300,1300] precision 0.7661595158240058 [0.767388,0.764931] predictive_accuracy 0.7661538461538462 prior_entropy 1 recall 0.7661538461538462 [0.763846,0.768462] relative_absolute_error 0.46579994979881884 root_mean_prior_squared_error 0.5 root_mean_squared_error 0.4506890760465503 root_relative_squared_error 0.9013781520931006 total_cost 0 area_under_roc_curve 0.8350295857988166 [0.83503,0.83503] area_under_roc_curve 0.8423076923076923 [0.842308,0.842308] area_under_roc_curve 0.8225147928994083 [0.822515,0.822515] area_under_roc_curve 0.8117751479289941 [0.811775,0.811775] area_under_roc_curve 0.8343786982248521 [0.834379,0.834379] area_under_roc_curve 0.7839644970414201 [0.783964,0.783964] area_under_roc_curve 0.7791420118343195 [0.779142,0.779142] area_under_roc_curve 0.7293491124260355 [0.729349,0.729349] area_under_roc_curve 0.8065384615384615 [0.806538,0.806538] area_under_roc_curve 0.8272189349112427 [0.827219,0.827219] 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 0.7999881649801763 [0.79845,0.801527] f_measure 0.8036108354685348 [0.796813,0.810409] f_measure 0.7997037037037037 [0.792,0.807407] f_measure 0.7614114025220532 [0.755906,0.766917] f_measure 0.7922954020947984 [0.790698,0.793893] f_measure 0.7423038802349148 [0.743295,0.741313] f_measure 0.7192266157783399 [0.720307,0.718147] f_measure 0.6880877975088494 [0.698885,0.677291] f_measure 0.7687381404174574 [0.779412,0.758065] f_measure 0.7846153846153847 [0.784615,0.784615] kappa 0.6000000000000001 kappa 0.6076923076923078 kappa 0.6000000000000001 kappa 0.523076923076923 kappa 0.5846153846153845 kappa 0.48461538461538467 kappa 0.43846153846153846 kappa 0.3769230769230769 kappa 0.5384615384615385 kappa 0.5692307692307692 kb_relative_information_score 159.27219741707177 kb_relative_information_score 157.14739835291886 kb_relative_information_score 152.28463330105382 kb_relative_information_score 140.16254935308262 kb_relative_information_score 151.80738904963266 kb_relative_information_score 125.57522566603137 kb_relative_information_score 118.37230599214485 kb_relative_information_score 97.62383739041901 kb_relative_information_score 139.00498897091882 kb_relative_information_score 149.19756724135152 mean_absolute_error 0.19394340702033006 mean_absolute_error 0.1974974215076025 mean_absolute_error 0.20933024805762362 mean_absolute_error 0.22997160079739265 mean_absolute_error 0.20993603210514977 mean_absolute_error 0.25823942774169023 mean_absolute_error 0.27212351311333205 mean_absolute_error 0.3115726411597451 mean_absolute_error 0.2332012111819805 mean_absolute_error 0.2131842463092464 mean_prior_absolute_error 0.5 mean_prior_absolute_error 0.5 mean_prior_absolute_error 0.5 mean_prior_absolute_error 0.5 mean_prior_absolute_error 0.5 mean_prior_absolute_error 0.5 mean_prior_absolute_error 0.5 mean_prior_absolute_error 0.5 mean_prior_absolute_error 0.5 mean_prior_absolute_error 0.5 number_of_instances 260 [130,130] number_of_instances 260 [130,130] number_of_instances 260 [130,130] number_of_instances 260 [130,130] number_of_instances 260 [130,130] number_of_instances 260 [130,130] number_of_instances 260 [130,130] number_of_instances 260 [130,130] number_of_instances 260 [130,130] number_of_instances 260 [130,130] precision 0.8000710227272727 [0.804688,0.795455] precision 0.8053094714311196 [0.826446,0.784173] precision 0.8017857142857143 [0.825,0.778571] precision 0.7620967741935483 [0.774194,0.75] precision 0.792376893939394 [0.796875,0.787879] precision 0.7423220308894017 [0.740458,0.744186] precision 0.7192437422332681 [0.717557,0.72093] precision 0.6893691658243654 [0.676259,0.702479] precision 0.771544521365481 [0.746479,0.79661] precision 0.7846153846153846 [0.784615,0.784615] predictive_accuracy 0.8 predictive_accuracy 0.8038461538461539 predictive_accuracy 0.8 predictive_accuracy 0.7615384615384616 predictive_accuracy 0.7923076923076923 predictive_accuracy 0.7423076923076922 predictive_accuracy 0.7192307692307692 predictive_accuracy 0.6884615384615383 predictive_accuracy 0.7692307692307692 predictive_accuracy 0.7846153846153847 prior_entropy 1 prior_entropy 1 prior_entropy 1 prior_entropy 1 prior_entropy 1 prior_entropy 1 prior_entropy 1 prior_entropy 1 prior_entropy 1 prior_entropy 1 recall 0.8 [0.792308,0.807692] recall 0.8038461538461539 [0.769231,0.838462] recall 0.8 [0.761538,0.838462] recall 0.7615384615384615 [0.738462,0.784615] recall 0.7923076923076923 [0.784615,0.8] recall 0.7423076923076923 [0.746154,0.738462] recall 0.7192307692307692 [0.723077,0.715385] recall 0.6884615384615385 [0.723077,0.653846] recall 0.7692307692307693 [0.815385,0.723077] recall 0.7846153846153846 [0.784615,0.784615] relative_absolute_error 0.3878868140406601 relative_absolute_error 0.394994843015205 relative_absolute_error 0.41866049611524725 relative_absolute_error 0.45994320159478536 relative_absolute_error 0.41987206421029954 relative_absolute_error 0.5164788554833805 relative_absolute_error 0.5442470262266641 relative_absolute_error 0.6231452823194902 relative_absolute_error 0.46640242236396096 relative_absolute_error 0.4263684926184928 root_mean_prior_squared_error 0.5 root_mean_prior_squared_error 0.5 root_mean_prior_squared_error 0.5 root_mean_prior_squared_error 0.5 root_mean_prior_squared_error 0.5 root_mean_prior_squared_error 0.5 root_mean_prior_squared_error 0.5 root_mean_prior_squared_error 0.5 root_mean_prior_squared_error 0.5 root_mean_prior_squared_error 0.5 root_mean_squared_error 0.4164968275594177 root_mean_squared_error 0.41473938889401424 root_mean_squared_error 0.42472045742305203 root_mean_squared_error 0.44689509062004773 root_mean_squared_error 0.4191731014522228 root_mean_squared_error 0.48120230115063983 root_mean_squared_error 0.48583449991560324 root_mean_squared_error 0.5299008835278113 root_mean_squared_error 0.44668719088134146 root_mean_squared_error 0.4266193594443799 root_relative_squared_error 0.8329936551188354 root_relative_squared_error 0.8294787777880285 root_relative_squared_error 0.8494409148461041 root_relative_squared_error 0.8937901812400955 root_relative_squared_error 0.8383462029044456 root_relative_squared_error 0.9624046023012797 root_relative_squared_error 0.9716689998312065 root_relative_squared_error 1.0598017670556226 root_relative_squared_error 0.8933743817626829 root_relative_squared_error 0.8532387188887598 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 2054.5261860024766 usercpu_time_millis 1898.3143600016774 usercpu_time_millis 1944.3174209955032 usercpu_time_millis 1876.3234429970908 usercpu_time_millis 1926.0301900030754 usercpu_time_millis 1923.3763400006865 usercpu_time_millis 1936.8241890006175 usercpu_time_millis 2202.118465997046 usercpu_time_millis 1931.2683770040167 usercpu_time_millis 1931.1093499964045 usercpu_time_millis_testing 4.624463999789441 usercpu_time_millis_testing 4.588882999087218 usercpu_time_millis_testing 4.479248997085961 usercpu_time_millis_testing 4.590607997670304 usercpu_time_millis_testing 4.614796001987997 usercpu_time_millis_testing 4.460915999516146 usercpu_time_millis_testing 4.573222999169957 usercpu_time_millis_testing 4.589704996760702 usercpu_time_millis_testing 4.481792002479779 usercpu_time_millis_testing 5.314107998856343 usercpu_time_millis_training 2049.901722002687 usercpu_time_millis_training 1893.7254770025902 usercpu_time_millis_training 1939.8381719984172 usercpu_time_millis_training 1871.7328349994204 usercpu_time_millis_training 1921.4153940010874 usercpu_time_millis_training 1918.9154240011703 usercpu_time_millis_training 1932.2509660014475 usercpu_time_millis_training 2197.528761000285 usercpu_time_millis_training 1926.7865850015369 usercpu_time_millis_training 1925.7952419975481