10126270 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) 8051682 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 14 8783 min_weight_fraction_leaf 0.0 8783 presort false 8783 random_state 1417 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 21173078 description https://api.openml.org/data/download/21173078/description.xml -1 21173079 predictions https://api.openml.org/data/download/21173079/predictions.arff area_under_roc_curve 0.9394093055555557 [0.994044,0.906711,0.966867,0.945375,0.915125,0.951063,0.889494,0.971358,0.980225,0.873831] average_cost 0 f_measure 0.7528573732658161 [0.955665,0.672897,0.895288,0.769976,0.688442,0.829016,0.495,0.835749,0.937343,0.449198] kappa 0.7266666666666667 kb_relative_information_score 1527.8917090229133 mean_absolute_error 0.057470397416657 mean_prior_absolute_error 0.18000000000000554 number_of_instances 2000 [200,200,200,200,200,200,200,200,200,200] precision 0.7537368406771701 [0.941748,0.631579,0.93956,0.746479,0.691919,0.860215,0.495,0.808411,0.939698,0.482759] predictive_accuracy 0.754 prior_entropy 3.321928094887362 recall 0.754 [0.97,0.72,0.855,0.795,0.685,0.8,0.495,0.865,0.935,0.42] relative_absolute_error 0.31927998564808463 root_mean_prior_squared_error 0.3000000000000046 root_mean_squared_error 0.18907647049606305 root_relative_squared_error 0.6302549016535338 total_cost 0 area_under_roc_curve 0.9441666666666666 [1,0.965556,0.964444,0.933194,0.931944,0.997083,0.855139,0.967917,0.9975,0.828889] area_under_roc_curve 0.9094027777777778 [0.974444,0.912778,0.917639,0.930556,0.81875,0.896667,0.841389,0.988056,0.948333,0.865417] area_under_roc_curve 0.934888888888889 [0.998889,0.898472,0.945139,0.869167,0.972222,0.989583,0.901667,0.945972,0.999722,0.828056] area_under_roc_curve 0.9266111111111112 [0.997361,0.861111,0.971806,0.987778,0.910417,0.879444,0.835694,0.939722,0.974583,0.908194] area_under_roc_curve 0.9375000000000003 [0.996944,0.901111,0.966111,0.934444,0.922639,0.967639,0.924722,0.929167,0.996528,0.835694] area_under_roc_curve 0.9512638888888888 [1,0.944444,0.998472,0.962778,0.934167,0.935833,0.891111,0.988194,0.99875,0.858889] area_under_roc_curve 0.9513194444444444 [0.999722,0.893472,0.9475,0.960694,0.954722,0.978194,0.94375,0.986806,0.974306,0.874028] area_under_roc_curve 0.9416666666666668 [0.973472,0.911667,0.999444,0.940417,0.858889,0.993611,0.921528,0.989444,0.946389,0.881806] area_under_roc_curve 0.9675 [0.999722,0.892083,0.998333,0.991944,0.956806,0.9425,0.960139,0.990556,1,0.942917] area_under_roc_curve 0.933111111111111 [1,0.892222,0.963611,0.941667,0.895972,0.937917,0.821111,0.9925,0.969306,0.916806] 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 0.7450919594226393 [0.97561,0.652174,0.842105,0.820513,0.790698,0.923077,0.47619,0.789474,0.878049,0.30303] 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 0.7655152374416008 [0.904762,0.651163,0.923077,0.826087,0.634146,0.777778,0.585366,0.810811,0.947368,0.594595] f_measure 0.7080861660191409 [0.97561,0.595745,0.888889,0.702703,0.619048,0.842105,0.363636,0.727273,0.97561,0.390244] 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 0.7537603366673133 [0.95,0.651163,0.9,0.651163,0.628571,0.9,0.564103,0.863636,0.864865,0.564103] f_measure 0.8025867780160449 [0.95,0.702703,0.894737,0.826087,0.8,0.823529,0.585366,0.888889,0.97561,0.578947] 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 0.7388888888888889 kappa 0.6777777777777777 kappa 0.7611111111111112 kappa 0.7666666666666667 kappa 0.7277777777777777 kappa 0.7833333333333334 kappa 0.7166666666666667 kb_relative_information_score 154.3700400536099 kb_relative_information_score 143.3567101202949 kb_relative_information_score 149.5831550569152 kb_relative_information_score 152.78667194199016 kb_relative_information_score 149.14957798504415 kb_relative_information_score 155.0943336338638 kb_relative_information_score 157.74153332895793 kb_relative_information_score 151.72790052688612 kb_relative_information_score 163.9649049430146 kb_relative_information_score 150.1168814323537 mean_absolute_error 0.0541800585620837 mean_absolute_error 0.06669528558592354 mean_absolute_error 0.06047213760391202 mean_absolute_error 0.0560604488777476 mean_absolute_error 0.06135862851544735 mean_absolute_error 0.055661662603523177 mean_absolute_error 0.052844084578655484 mean_absolute_error 0.06039531780830403 mean_absolute_error 0.0475723485610499 mean_absolute_error 0.05946400146991849 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 0.7476434066823083 [0.952381,0.576923,0.888889,0.842105,0.73913,0.947368,0.454545,0.833333,0.857143,0.384615] 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 0.7745357622814211 [0.863636,0.608696,0.947368,0.730769,0.619048,0.875,0.571429,0.882353,1,0.647059] precision 0.7176941794588854 [0.952381,0.518519,1,0.764706,0.590909,0.888889,0.461538,0.666667,0.952381,0.380952] 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 0.7591462511778166 [0.95,0.608696,0.9,0.608696,0.733333,0.9,0.578947,0.791667,0.941176,0.578947] precision 0.8124840192487252 [0.95,0.764706,0.944444,0.730769,0.8,1,0.571429,0.8,0.952381,0.611111] 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 0.765 predictive_accuracy 0.71 predictive_accuracy 0.785 predictive_accuracy 0.79 predictive_accuracy 0.755 predictive_accuracy 0.805 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 [1,0.75,0.8,0.8,0.85,0.9,0.5,0.75,0.9,0.25] 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 0.765 [0.95,0.7,0.9,0.95,0.65,0.7,0.6,0.75,0.9,0.55] recall 0.71 [1,0.7,0.8,0.65,0.65,0.8,0.3,0.8,1,0.4] 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 0.755 [0.95,0.7,0.9,0.7,0.55,0.9,0.55,0.95,0.8,0.55] recall 0.805 [0.95,0.65,0.85,0.95,0.8,0.7,0.6,1,1,0.55] recall 0.745 [1,0.7,0.9,0.8,0.6,0.8,0.5,1,0.95,0.2] relative_absolute_error 0.3010003253449098 relative_absolute_error 0.3705293643662423 relative_absolute_error 0.3359563200217338 relative_absolute_error 0.31144693820970926 relative_absolute_error 0.3408812695302634 relative_absolute_error 0.30923145890846243 relative_absolute_error 0.29357824765919743 relative_absolute_error 0.3355295433794672 relative_absolute_error 0.2642908253391664 relative_absolute_error 0.3303555637217698 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 0.1885605687575288 root_mean_squared_error 0.2114442826014611 root_mean_squared_error 0.19313190635728192 root_mean_squared_error 0.19052704156872657 root_mean_squared_error 0.19798313669421566 root_mean_squared_error 0.1802384802058278 root_mean_squared_error 0.1781791639661352 root_mean_squared_error 0.18861354259721222 root_mean_squared_error 0.1619023284223039 root_mean_squared_error 0.19600096520643986 root_relative_squared_error 0.6285352291917631 root_relative_squared_error 0.704814275338204 root_relative_squared_error 0.6437730211909402 root_relative_squared_error 0.6350901385624222 root_relative_squared_error 0.6599437889807193 root_relative_squared_error 0.6007949340194263 root_relative_squared_error 0.5939305465537843 root_relative_squared_error 0.6287118086573744 root_relative_squared_error 0.5396744280743466 root_relative_squared_error 0.6533365506881332 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 2559.9632630000997 usercpu_time_millis 2397.2084950000863 usercpu_time_millis 2402.5658469981863 usercpu_time_millis 2387.78643799742 usercpu_time_millis 2398.0489790010324 usercpu_time_millis 2394.2203520018666 usercpu_time_millis 2420.3106700006174 usercpu_time_millis 2431.500791997678 usercpu_time_millis 2425.377388000925 usercpu_time_millis 2414.640164002776 usercpu_time_millis_testing 1.7130870000983123 usercpu_time_millis_testing 1.6916450003918726 usercpu_time_millis_testing 1.6762749983172398 usercpu_time_millis_testing 1.6285469973809086 usercpu_time_millis_testing 1.746537000144599 usercpu_time_millis_testing 1.6881000010471325 usercpu_time_millis_testing 1.6896320012165233 usercpu_time_millis_testing 1.701623998087598 usercpu_time_millis_testing 1.6456390003440902 usercpu_time_millis_testing 1.5578470010950696 usercpu_time_millis_training 2558.2501760000014 usercpu_time_millis_training 2395.5168499996944 usercpu_time_millis_training 2400.889571999869 usercpu_time_millis_training 2386.157891000039 usercpu_time_millis_training 2396.302442000888 usercpu_time_millis_training 2392.5322520008194 usercpu_time_millis_training 2418.621037999401 usercpu_time_millis_training 2429.7991679995903 usercpu_time_millis_training 2423.7317490005807 usercpu_time_millis_training 2413.082317001681