10064290 1 Jan van Rijn 14 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) 7989118 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 13 8783 min_samples_split 6 8783 min_weight_fraction_leaf 0.0 8783 presort false 8783 random_state 2196 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. 14 mfeat-fourier https://www.openml.org/data/download/14/dataset_14_mfeat-fourier.arff -1 21049115 description https://api.openml.org/data/download/21049115/description.xml -1 21049116 predictions https://api.openml.org/data/download/21049116/predictions.arff area_under_roc_curve 0.9399759722222224 [0.991196,0.901419,0.967171,0.9457,0.926078,0.95185,0.886433,0.974144,0.979704,0.876064] average_cost 0 f_measure 0.7519916553538804 [0.955665,0.668224,0.895288,0.772947,0.688442,0.831169,0.479592,0.835749,0.937343,0.455497] kappa 0.7255555555555556 kb_relative_information_score 1527.5077046151853 mean_absolute_error 0.05749568417039772 mean_prior_absolute_error 0.18000000000000554 number_of_instances 2000 [200,200,200,200,200,200,200,200,200,200] precision 0.7528663621788934 [0.941748,0.627193,0.93956,0.747664,0.691919,0.864865,0.489583,0.808411,0.939698,0.478022] predictive_accuracy 0.753 prior_entropy 3.321928094887362 recall 0.753 [0.97,0.715,0.855,0.8,0.685,0.8,0.47,0.865,0.935,0.435] relative_absolute_error 0.31942046761331083 root_mean_prior_squared_error 0.3000000000000046 root_mean_squared_error 0.1892939100028098 root_relative_squared_error 0.6309797000093563 total_cost 0 area_under_roc_curve 0.9389444444444444 [0.996806,0.939444,0.964444,0.933194,0.931389,0.994861,0.854583,0.967917,0.9975,0.809306] area_under_roc_curve 0.9147361111111111 [0.974444,0.911944,0.919861,0.93,0.870833,0.8975,0.840972,0.988056,0.948333,0.865417] area_under_roc_curve 0.9410000000000001 [0.974028,0.898056,0.945139,0.870278,0.977917,0.990694,0.90625,0.94625,0.997083,0.904306] area_under_roc_curve 0.926736111111111 [0.995,0.859306,0.971806,0.987778,0.914722,0.882639,0.835694,0.965556,0.974583,0.880278] area_under_roc_curve 0.9421527777777778 [1,0.901667,0.966111,0.936111,0.94875,0.97,0.928194,0.929167,0.996528,0.845] area_under_roc_curve 0.9516388888888889 [1,0.944722,0.998472,0.962778,0.935833,0.936111,0.891667,0.988194,0.99875,0.859861] area_under_roc_curve 0.9516249999999999 [0.999722,0.893472,0.9475,0.960972,0.957361,0.977083,0.943611,0.988194,0.974306,0.874028] area_under_roc_curve 0.9383750000000001 [0.973472,0.887917,0.999444,0.942639,0.860833,0.994028,0.916389,0.98625,0.944306,0.878472] area_under_roc_curve 0.9618194444444444 [0.999583,0.892083,0.998333,0.991111,0.955833,0.943056,0.923333,0.990556,1,0.924306] area_under_roc_curve 0.9357499999999999 [1,0.892222,0.962361,0.940833,0.919583,0.938472,0.821111,0.9975,0.969444,0.915972] 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 0.7464555957862757 [0.97561,0.652174,0.842105,0.820513,0.790698,0.923077,0.45,0.789474,0.878049,0.342857] f_measure 0.6984005747217751 [0.974359,0.697674,0.833333,0.780488,0.585366,0.648649,0.1875,0.829268,0.947368,0.5] f_measure 0.7328552095521478 [0.95,0.638298,0.918919,0.666667,0.755556,0.878049,0.409091,0.833333,0.97561,0.30303] f_measure 0.7608640746509032 [0.904762,0.604651,0.923077,0.826087,0.634146,0.777778,0.585366,0.810811,0.947368,0.594595] f_measure 0.7297570874573919 [0.97561,0.595745,0.888889,0.736842,0.619048,0.864865,0.4375,0.727273,0.97561,0.47619] f_measure 0.7749359065411768 [0.97561,0.782609,0.947368,0.837209,0.628571,0.857143,0.484848,0.790698,0.904762,0.540541] f_measure 0.7810601303458446 [0.974359,0.666667,0.923077,0.761905,0.75,0.761905,0.734694,0.863636,0.974359,0.4] f_measure 0.743247009080815 [0.95,0.651163,0.9,0.651163,0.628571,0.9,0.486486,0.863636,0.864865,0.536585] f_measure 0.7871824134460834 [0.95,0.702703,0.894737,0.826087,0.8,0.823529,0.473684,0.888889,0.97561,0.536585] f_measure 0.7389099817175219 [0.930233,0.7,0.878049,0.8,0.666667,0.864865,0.434783,0.952381,0.926829,0.235294] kappa 0.7222222222222222 kappa 0.6666666666666666 kappa 0.7055555555555556 kappa 0.7333333333333334 kappa 0.7 kappa 0.7611111111111112 kappa 0.7666666666666667 kappa 0.7166666666666667 kappa 0.7666666666666667 kappa 0.7166666666666667 kb_relative_information_score 153.50374297961426 kb_relative_information_score 143.47996075304528 kb_relative_information_score 151.0215603280212 kb_relative_information_score 151.59360775356063 kb_relative_information_score 152.22795669705857 kb_relative_information_score 155.50387116154855 kb_relative_information_score 158.02384864467984 kb_relative_information_score 151.58107030033162 kb_relative_information_score 160.5663338333977 kb_relative_information_score 150.00575216394247 mean_absolute_error 0.055795443177468325 mean_absolute_error 0.06669528558592352 mean_absolute_error 0.05931829145006587 mean_absolute_error 0.056220516751050775 mean_absolute_error 0.05826324390006274 mean_absolute_error 0.05488500176436234 mean_absolute_error 0.052396969194040105 mean_absolute_error 0.06028762550061172 mean_absolute_error 0.050784309064314775 mean_absolute_error 0.06031015531607232 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] precision 0.7487273227662244 [0.952381,0.576923,0.888889,0.842105,0.73913,0.947368,0.45,0.833333,0.857143,0.4] precision 0.7094663408841798 [1,0.652174,0.9375,0.761905,0.571429,0.705882,0.25,0.809524,1,0.40625] precision 0.7442194749694748 [0.95,0.555556,1,0.75,0.68,0.857143,0.375,0.9375,0.952381,0.384615] precision 0.7701879361944647 [0.863636,0.565217,0.947368,0.730769,0.619048,0.875,0.571429,0.882353,1,0.647059] precision 0.7437689217100981 [0.952381,0.518519,1,0.777778,0.590909,0.941176,0.583333,0.666667,0.952381,0.454545] precision 0.7785199199777204 [0.952381,0.692308,1,0.782609,0.733333,0.818182,0.615385,0.73913,0.863636,0.588235] precision 0.7914270197437167 [1,0.75,0.947368,0.727273,0.75,0.727273,0.62069,0.791667,1,0.6] precision 0.7486789063451468 [0.95,0.608696,0.9,0.608696,0.733333,0.9,0.529412,0.791667,0.941176,0.52381] precision 0.7966110033757093 [0.95,0.764706,0.944444,0.730769,0.8,1,0.5,0.8,0.952381,0.52381] precision 0.7402067029304882 [0.869565,0.7,0.857143,0.8,0.75,0.941176,0.384615,0.909091,0.904762,0.285714] predictive_accuracy 0.75 predictive_accuracy 0.7 predictive_accuracy 0.735 predictive_accuracy 0.76 predictive_accuracy 0.73 predictive_accuracy 0.785 predictive_accuracy 0.79 predictive_accuracy 0.745 predictive_accuracy 0.79 predictive_accuracy 0.745 prior_entropy 3.321928094887362 prior_entropy 3.321928094887362 prior_entropy 3.321928094887362 prior_entropy 3.321928094887362 prior_entropy 3.321928094887362 prior_entropy 3.321928094887362 prior_entropy 3.321928094887362 prior_entropy 3.321928094887362 prior_entropy 3.321928094887362 prior_entropy 3.321928094887362 recall 0.75 [1,0.75,0.8,0.8,0.85,0.9,0.45,0.75,0.9,0.3] recall 0.7 [0.95,0.75,0.75,0.8,0.6,0.6,0.15,0.85,0.9,0.65] recall 0.735 [0.95,0.75,0.85,0.6,0.85,0.9,0.45,0.75,1,0.25] recall 0.76 [0.95,0.65,0.9,0.95,0.65,0.7,0.6,0.75,0.9,0.55] recall 0.73 [1,0.7,0.8,0.7,0.65,0.8,0.35,0.8,1,0.5] recall 0.785 [1,0.9,0.9,0.9,0.55,0.9,0.4,0.85,0.95,0.5] recall 0.79 [0.95,0.6,0.9,0.8,0.75,0.8,0.9,0.95,0.95,0.3] recall 0.745 [0.95,0.7,0.9,0.7,0.55,0.9,0.45,0.95,0.8,0.55] recall 0.79 [0.95,0.65,0.85,0.95,0.8,0.7,0.45,1,1,0.55] recall 0.745 [1,0.7,0.9,0.8,0.6,0.8,0.5,1,0.95,0.2] relative_absolute_error 0.30997468431926883 relative_absolute_error 0.37052936436624223 relative_absolute_error 0.32954606361147737 relative_absolute_error 0.3123362041725047 relative_absolute_error 0.32368468833368225 relative_absolute_error 0.30491667646868 relative_absolute_error 0.2910942733002231 relative_absolute_error 0.3349312527811766 relative_absolute_error 0.2821350503573046 relative_absolute_error 0.33505641842262435 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_squared_error 0.19085044875492815 root_mean_squared_error 0.21054687463839133 root_mean_squared_error 0.18996556398915734 root_mean_squared_error 0.1932514482396332 root_mean_squared_error 0.19081112200936587 root_mean_squared_error 0.17936641061686961 root_mean_squared_error 0.17820303136824206 root_mean_squared_error 0.19046977999179723 root_mean_squared_error 0.17166583879035083 root_mean_squared_error 0.19506284745314934 root_relative_squared_error 0.6361681625164276 root_relative_squared_error 0.7018229154613048 root_relative_squared_error 0.6332185466305249 root_relative_squared_error 0.644171494132111 root_relative_squared_error 0.6360370733645533 root_relative_squared_error 0.5978880353895658 root_relative_squared_error 0.5940101045608072 root_relative_squared_error 0.6348992666393245 root_relative_squared_error 0.5722194626345032 root_relative_squared_error 0.6502094915104982 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 3038.624087000244 usercpu_time_millis 2798.595152999951 usercpu_time_millis 2838.967263000086 usercpu_time_millis 2844.2718030000833 usercpu_time_millis 2803.4274269994057 usercpu_time_millis 2827.36578299955 usercpu_time_millis 2855.9893259998717 usercpu_time_millis 2846.455896000407 usercpu_time_millis 2789.2710539999825 usercpu_time_millis 2812.1022109999103 usercpu_time_millis_testing 1.3952110002719564 usercpu_time_millis_testing 1.382132999424357 usercpu_time_millis_testing 1.3703040003747446 usercpu_time_millis_testing 1.5030620006655226 usercpu_time_millis_testing 1.50415799998882 usercpu_time_millis_testing 1.3935919996583834 usercpu_time_millis_testing 1.3868269998056348 usercpu_time_millis_testing 1.5084040005604038 usercpu_time_millis_testing 1.3870709999537212 usercpu_time_millis_testing 1.397394999912649 usercpu_time_millis_training 3037.228875999972 usercpu_time_millis_training 2797.2130200005267 usercpu_time_millis_training 2837.596958999711 usercpu_time_millis_training 2842.768740999418 usercpu_time_millis_training 2801.923268999417 usercpu_time_millis_training 2825.9721909998916 usercpu_time_millis_training 2854.602499000066 usercpu_time_millis_training 2844.9474919998465 usercpu_time_millis_training 2787.883983000029 usercpu_time_millis_training 2810.7048159999977