10065892 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) 7990735 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 "gini" 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 12 8783 min_samples_split 15 8783 min_weight_fraction_leaf 0.0 8783 presort false 8783 random_state 35320 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 21052319 description https://api.openml.org/data/download/21052319/description.xml -1 21052320 predictions https://api.openml.org/data/download/21052320/predictions.arff area_under_roc_curve 0.9288230555555557 [0.994321,0.903446,0.944837,0.942992,0.872324,0.950011,0.861287,0.960213,0.983126,0.875674] average_cost 0 f_measure 0.7379560625515615 [0.975369,0.660832,0.880407,0.790576,0.645161,0.791045,0.496487,0.77561,0.934726,0.429348] kappa 0.7083333333333334 kb_relative_information_score 1477.5814821555934 mean_absolute_error 0.06128901667758005 mean_prior_absolute_error 0.18000000000000554 number_of_instances 2000 [200,200,200,200,200,200,200,200,200,200] precision 0.7432043586123663 [0.961165,0.587549,0.896373,0.82967,0.697674,0.787129,0.46696,0.757143,0.978142,0.470238] predictive_accuracy 0.7375 prior_entropy 3.321928094887362 recall 0.7375 [0.99,0.755,0.865,0.755,0.6,0.795,0.53,0.795,0.895,0.395] relative_absolute_error 0.3404945370976565 root_mean_prior_squared_error 0.3000000000000046 root_mean_squared_error 0.19581166024478683 root_relative_squared_error 0.6527055341492795 total_cost 0 area_under_roc_curve 0.9395555555555556 [0.996667,0.960694,0.914028,0.940139,0.901389,0.996667,0.864444,0.929444,0.997222,0.894861] area_under_roc_curve 0.9250833333333334 [0.974444,0.914028,0.883194,0.987083,0.799722,0.957222,0.914028,0.951389,0.946944,0.922778] area_under_roc_curve 0.9075277777777778 [1,0.879444,0.959167,0.907778,0.864306,0.940556,0.773611,0.899444,0.997083,0.853889] area_under_roc_curve 0.9368749999999999 [1,0.837778,0.969583,0.982917,0.934306,0.917222,0.87875,0.982083,0.974583,0.891528] area_under_roc_curve 0.9312638888888888 [0.999167,0.888194,0.969722,0.9825,0.910417,0.881806,0.880972,0.982222,0.971806,0.845833] area_under_roc_curve 0.9452916666666666 [0.999722,0.927917,0.998611,0.911806,0.888889,0.963194,0.837361,0.98875,0.995833,0.940833] area_under_roc_curve 0.9164166666666667 [0.999583,0.961111,0.864583,0.903056,0.833056,0.925278,0.914167,0.958333,0.996806,0.808194] area_under_roc_curve 0.9327916666666667 [0.974861,0.930278,0.937361,0.90625,0.863056,0.989028,0.899722,0.995,0.952639,0.879722] area_under_roc_curve 0.9375000000000001 [1,0.844861,0.99625,0.981111,0.875139,0.960417,0.849167,0.983889,1,0.884167] area_under_roc_curve 0.9191666666666669 [0.999444,0.902361,0.960833,0.926111,0.865278,0.970139,0.804861,0.936389,0.982361,0.843889] 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 0.7254468603180851 [0.97561,0.641509,0.829268,0.833333,0.648649,0.894737,0.478261,0.702703,0.947368,0.30303] f_measure 0.7328635389249772 [0.926829,0.717949,0.8,0.790698,0.685714,0.8,0.439024,0.8,0.947368,0.421053] f_measure 0.6651425190027446 [1,0.54902,0.888889,0.702703,0.608696,0.789474,0.391304,0.451613,0.97561,0.294118] f_measure 0.7506091339273857 [1,0.608696,0.883721,0.780488,0.684211,0.764706,0.590909,0.731707,0.947368,0.514286] f_measure 0.7173017482330257 [0.97561,0.619048,0.894737,0.820513,0.628571,0.697674,0.410256,0.755556,0.95,0.421053] f_measure 0.7675149808280815 [0.97561,0.8,0.952381,0.764706,0.7,0.837209,0.521739,0.863636,0.947368,0.3125] f_measure 0.7501438305832799 [0.97561,0.64,0.833333,0.789474,0.647059,0.666667,0.681818,0.790698,0.947368,0.529412] f_measure 0.7578818169479272 [0.974359,0.625,0.894737,0.809524,0.594595,0.820513,0.585366,0.904762,0.857143,0.512821] f_measure 0.7641478272303418 [1,0.736842,0.952381,0.810811,0.588235,0.761905,0.4,0.826087,1,0.565217] f_measure 0.7342147232930288 [0.952381,0.72,0.864865,0.8,0.666667,0.894737,0.444444,0.829268,0.810811,0.358974] kappa 0.6944444444444444 kappa 0.7055555555555556 kappa 0.6277777777777779 kappa 0.7222222222222222 kappa 0.6888888888888889 kappa 0.75 kappa 0.7222222222222222 kappa 0.7277777777777777 kappa 0.7444444444444445 kappa 0.7 kb_relative_information_score 148.46434427267886 kb_relative_information_score 146.0123917804069 kb_relative_information_score 140.592230367436 kb_relative_information_score 152.0054929558278 kb_relative_information_score 148.12933328354515 kb_relative_information_score 152.80585220783016 kb_relative_information_score 149.1640229702209 kb_relative_information_score 147.71490176672958 kb_relative_information_score 153.00630979361517 kb_relative_information_score 139.6866027573212 mean_absolute_error 0.05978474534712081 mean_absolute_error 0.06379443739207499 mean_absolute_error 0.06689545155828297 mean_absolute_error 0.056214153858136905 mean_absolute_error 0.06012968665583083 mean_absolute_error 0.058272148113324575 mean_absolute_error 0.05970444326560052 mean_absolute_error 0.06148581531127971 mean_absolute_error 0.05692366419587947 mean_absolute_error 0.06968562107826808 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 0.7437281264487146 [0.952381,0.515152,0.809524,0.9375,0.705882,0.944444,0.423077,0.764706,1,0.384615] precision 0.7373750317823543 [0.904762,0.736842,0.8,0.73913,0.8,0.72,0.428571,0.8,1,0.444444] precision 0.6880154949414912 [1,0.451613,1,0.764706,0.538462,0.833333,0.346154,0.636364,0.952381,0.357143] precision 0.7633199288634072 [1,0.538462,0.826087,0.761905,0.722222,0.928571,0.541667,0.714286,1,0.6] precision 0.7210844073292586 [0.952381,0.590909,0.944444,0.842105,0.733333,0.652174,0.421053,0.68,0.95,0.444444] precision 0.774252378056726 [0.952381,0.8,0.909091,0.928571,0.7,0.782609,0.461538,0.791667,1,0.416667] precision 0.7685613118765293 [0.952381,0.533333,0.9375,0.833333,0.785714,0.636364,0.625,0.73913,1,0.642857] precision 0.7703430814111928 [1,0.535714,0.944444,0.772727,0.647059,0.842105,0.571429,0.863636,1,0.526316] precision 0.7708215967039496 [1,0.777778,0.909091,0.882353,0.714286,0.727273,0.466667,0.730769,1,0.5] precision 0.7538342960788782 [0.909091,0.6,0.941176,0.933333,0.75,0.944444,0.4,0.809524,0.882353,0.368421] predictive_accuracy 0.725 predictive_accuracy 0.735 predictive_accuracy 0.665 predictive_accuracy 0.75 predictive_accuracy 0.72 predictive_accuracy 0.775 predictive_accuracy 0.75 predictive_accuracy 0.755 predictive_accuracy 0.77 predictive_accuracy 0.73 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 0.725 [1,0.85,0.85,0.75,0.6,0.85,0.55,0.65,0.9,0.25] recall 0.735 [0.95,0.7,0.8,0.85,0.6,0.9,0.45,0.8,0.9,0.4] recall 0.665 [1,0.7,0.8,0.65,0.7,0.75,0.45,0.35,1,0.25] recall 0.75 [1,0.7,0.95,0.8,0.65,0.65,0.65,0.75,0.9,0.45] recall 0.72 [1,0.65,0.85,0.8,0.55,0.75,0.4,0.85,0.95,0.4] recall 0.775 [1,0.8,1,0.65,0.7,0.9,0.6,0.95,0.9,0.25] recall 0.75 [1,0.8,0.75,0.75,0.55,0.7,0.75,0.85,0.9,0.45] recall 0.755 [0.95,0.75,0.85,0.85,0.55,0.8,0.6,0.95,0.75,0.5] recall 0.77 [1,0.7,1,0.75,0.5,0.8,0.35,0.95,1,0.65] recall 0.73 [1,0.9,0.8,0.7,0.6,0.85,0.5,0.85,0.75,0.35] relative_absolute_error 0.3321374741506715 relative_absolute_error 0.35441354106708367 relative_absolute_error 0.37164139754601694 relative_absolute_error 0.3123008547674276 relative_absolute_error 0.3340538147546161 relative_absolute_error 0.3237341561851369 relative_absolute_error 0.3316913514755588 relative_absolute_error 0.34158786284044323 relative_absolute_error 0.31624257886599744 relative_absolute_error 0.38714233932371195 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 0.1955494130708672 root_mean_squared_error 0.20056241738227015 root_mean_squared_error 0.21134437259973118 root_mean_squared_error 0.18784897229186404 root_mean_squared_error 0.19850991680885338 root_mean_squared_error 0.18255798720280053 root_mean_squared_error 0.19525357407155589 root_mean_squared_error 0.19264854744602844 root_mean_squared_error 0.18445328046800824 root_mean_squared_error 0.20738728741113116 root_relative_squared_error 0.6518313769028912 root_relative_squared_error 0.6685413912742342 root_relative_squared_error 0.7044812419991043 root_relative_squared_error 0.6261632409728805 root_relative_squared_error 0.6616997226961785 root_relative_squared_error 0.6085266240093355 root_relative_squared_error 0.6508452469051866 root_relative_squared_error 0.6421618248200951 root_relative_squared_error 0.6148442682266945 root_relative_squared_error 0.6912909580371043 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 2549.59597099878 usercpu_time_millis 2260.8419400003186 usercpu_time_millis 2361.700765999558 usercpu_time_millis 2426.375814999119 usercpu_time_millis 2461.5282049999223 usercpu_time_millis 2437.8405589977774 usercpu_time_millis 2446.454231001553 usercpu_time_millis 2457.6802299998235 usercpu_time_millis 2773.569799001052 usercpu_time_millis 2697.5124850014254 usercpu_time_millis_testing 1.3999709990457632 usercpu_time_millis_testing 1.3753900002484443 usercpu_time_millis_testing 1.6364579987566685 usercpu_time_millis_testing 1.7368899989378406 usercpu_time_millis_testing 1.6407940001954557 usercpu_time_millis_testing 1.7437689984944882 usercpu_time_millis_testing 1.5473000003112247 usercpu_time_millis_testing 1.557719999254914 usercpu_time_millis_testing 1.7254040012630867 usercpu_time_millis_testing 1.4794230010011233 usercpu_time_millis_training 2548.1959999997343 usercpu_time_millis_training 2259.46655000007 usercpu_time_millis_training 2360.0643080008012 usercpu_time_millis_training 2424.638925000181 usercpu_time_millis_training 2459.887410999727 usercpu_time_millis_training 2436.096789999283 usercpu_time_millis_training 2444.906931001242 usercpu_time_millis_training 2456.1225100005686 usercpu_time_millis_training 2771.844394999789 usercpu_time_millis_training 2696.0330620004243