10147459 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) 8073082 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 4 8783 min_samples_split 11 8783 min_weight_fraction_leaf 0.0 8783 presort false 8783 random_state 14419 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 21215457 description https://api.openml.org/data/download/21215457/description.xml -1 21215458 predictions https://api.openml.org/data/download/21215458/predictions.arff area_under_roc_curve 0.9011068055555554 [0.993839,0.850758,0.94605,0.918335,0.863726,0.920879,0.795729,0.953301,0.980367,0.788083] average_cost 0 f_measure 0.751322955612765 [0.975369,0.678663,0.863636,0.807882,0.665012,0.827411,0.508159,0.797101,0.94026,0.449735] kappa 0.7233333333333334 kb_relative_information_score 1508.9574893578067 mean_absolute_error 0.053226507936508245 mean_prior_absolute_error 0.18000000000000554 number_of_instances 2000 [200,200,200,200,200,200,200,200,200,200] precision 0.7531364977537379 [0.961165,0.698413,0.872449,0.796117,0.660099,0.840206,0.475983,0.771028,0.978378,0.477528] predictive_accuracy 0.7509999999999999 prior_entropy 3.321928094887362 recall 0.751 [0.99,0.66,0.855,0.82,0.67,0.815,0.545,0.825,0.905,0.425] relative_absolute_error 0.2957028218694811 root_mean_prior_squared_error 0.3000000000000046 root_mean_squared_error 0.20371476930021723 root_relative_squared_error 0.6790492310007136 total_cost 0 area_under_roc_curve 0.9022083333333332 [0.999861,0.881111,0.935556,0.944306,0.825972,0.973194,0.771944,0.939722,0.999028,0.751389] area_under_roc_curve 0.9073055555555556 [0.972083,0.853056,0.917083,0.944444,0.848056,0.910556,0.829306,0.96375,0.974028,0.860694] area_under_roc_curve 0.8845694444444443 [1,0.927639,0.9225,0.836667,0.904444,0.890278,0.697361,0.9175,0.997222,0.752083] area_under_roc_curve 0.9169166666666666 [1,0.776111,0.974028,0.972639,0.909444,0.944861,0.841667,0.886528,0.974722,0.889167] area_under_roc_curve 0.8911805555555555 [0.997222,0.7475,0.97125,0.939306,0.872361,0.85625,0.856111,0.946667,0.971528,0.753611] area_under_roc_curve 0.919888888888889 [1,0.963611,0.996806,0.890972,0.908194,0.915972,0.835972,0.965556,0.999583,0.722222] area_under_roc_curve 0.9000277777777778 [1,0.89625,0.896389,0.888194,0.870694,0.908889,0.782917,0.988472,0.99875,0.769722] area_under_roc_curve 0.8886111111111111 [0.974583,0.848056,0.915278,0.906111,0.771806,0.942778,0.809861,0.962361,0.944722,0.810556] area_under_roc_curve 0.9136666666666667 [1,0.788056,0.989306,0.971667,0.875278,0.917917,0.772361,0.986667,1,0.835417] area_under_roc_curve 0.8886527777777777 [0.994444,0.83125,0.944167,0.890972,0.853056,0.948611,0.759722,0.978056,0.942917,0.743333] 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 0.7572856661239205 [0.97561,0.714286,0.772727,0.85,0.666667,0.947368,0.5,0.777778,0.947368,0.421053] f_measure 0.7436868798707245 [0.926829,0.666667,0.833333,0.9,0.588235,0.744186,0.521739,0.808511,0.947368,0.5] f_measure 0.7340063742389324 [1,0.714286,0.918919,0.666667,0.744186,0.777778,0.409091,0.756757,0.952381,0.4] f_measure 0.8005025421537049 [1,0.611111,0.95,0.883721,0.68,0.918919,0.611111,0.756757,0.974359,0.619048] f_measure 0.7364977876316746 [0.97561,0.571429,0.888889,0.818182,0.666667,0.717949,0.52381,0.765957,0.95,0.486486] f_measure 0.7752569699119763 [0.97561,0.809524,0.926829,0.810811,0.769231,0.829268,0.571429,0.8,0.947368,0.3125] f_measure 0.7225262283640644 [0.97561,0.666667,0.789474,0.714286,0.594595,0.780488,0.511628,0.829268,0.974359,0.388889] f_measure 0.7229719464541986 [0.974359,0.681818,0.8,0.714286,0.578947,0.85,0.511628,0.8,0.857143,0.461538] f_measure 0.7689953593878355 [1,0.645161,0.904762,0.857143,0.666667,0.829268,0.457143,0.818182,1,0.511628] f_measure 0.739117887684517 [0.952381,0.666667,0.857143,0.864865,0.666667,0.894737,0.468085,0.844444,0.833333,0.342857] kappa 0.7277777777777777 kappa 0.7166666666666667 kappa 0.7 kappa 0.7777777777777778 kappa 0.7111111111111111 kappa 0.7555555555555555 kappa 0.6944444444444444 kappa 0.6888888888888889 kappa 0.75 kappa 0.7111111111111111 kb_relative_information_score 151.30748059535685 kb_relative_information_score 151.86052112132805 kb_relative_information_score 146.60619661558482 kb_relative_information_score 157.02185403839923 kb_relative_information_score 146.83557345417847 kb_relative_information_score 159.16586665595477 kb_relative_information_score 146.99529869922864 kb_relative_information_score 146.23023384908646 kb_relative_information_score 155.66716527368828 kb_relative_information_score 147.26729905502825 mean_absolute_error 0.05338888888888887 mean_absolute_error 0.05277222222222223 mean_absolute_error 0.05562936507936505 mean_absolute_error 0.04751785714285714 mean_absolute_error 0.05868571428571427 mean_absolute_error 0.04492579365079363 mean_absolute_error 0.056378571428571396 mean_absolute_error 0.05794484126984125 mean_absolute_error 0.047303968253968244 mean_absolute_error 0.05771785714285713 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 0.7654520771626036 [0.952381,0.681818,0.708333,0.85,0.684211,1,0.458333,0.875,1,0.444444] precision 0.7564152484518618 [0.904762,0.684211,0.9375,0.9,0.714286,0.695652,0.461538,0.703704,1,0.5625] precision 0.7444301202902629 [1,0.681818,1,0.684211,0.695652,0.875,0.375,0.823529,0.909091,0.4] precision 0.8132192125862201 [1,0.6875,0.95,0.826087,0.566667,1,0.6875,0.823529,1,0.590909] precision 0.7436178681999117 [0.952381,0.666667,1,0.75,0.684211,0.736842,0.5,0.666667,0.95,0.529412] precision 0.7810645852137259 [0.952381,0.772727,0.904762,0.882353,0.789474,0.809524,0.482759,0.8,1,0.416667] precision 0.7238144368419305 [0.952381,0.636364,0.833333,0.681818,0.647059,0.761905,0.478261,0.809524,1,0.4375] precision 0.7319874373020826 [1,0.625,0.8,0.681818,0.611111,0.85,0.478261,0.8,1,0.473684] precision 0.7798390739695087 [1,0.909091,0.863636,0.818182,0.636364,0.809524,0.533333,0.75,1,0.478261] precision 0.750416468607645 [0.909091,0.75,0.818182,0.941176,0.636364,0.944444,0.407407,0.76,0.9375,0.4] predictive_accuracy 0.755 predictive_accuracy 0.745 predictive_accuracy 0.73 predictive_accuracy 0.8 predictive_accuracy 0.74 predictive_accuracy 0.78 predictive_accuracy 0.725 predictive_accuracy 0.72 predictive_accuracy 0.775 predictive_accuracy 0.74 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 0.755 [1,0.75,0.85,0.85,0.65,0.9,0.55,0.7,0.9,0.4] recall 0.745 [0.95,0.65,0.75,0.9,0.5,0.8,0.6,0.95,0.9,0.45] recall 0.73 [1,0.75,0.85,0.65,0.8,0.7,0.45,0.7,1,0.4] recall 0.8 [1,0.55,0.95,0.95,0.85,0.85,0.55,0.7,0.95,0.65] recall 0.74 [1,0.5,0.8,0.9,0.65,0.7,0.55,0.9,0.95,0.45] recall 0.78 [1,0.85,0.95,0.75,0.75,0.85,0.7,0.8,0.9,0.25] recall 0.725 [1,0.7,0.75,0.75,0.55,0.8,0.55,0.85,0.95,0.35] recall 0.72 [0.95,0.75,0.8,0.75,0.55,0.85,0.55,0.8,0.75,0.45] recall 0.775 [1,0.5,0.95,0.9,0.7,0.85,0.4,0.9,1,0.55] recall 0.74 [1,0.6,0.9,0.8,0.7,0.85,0.55,0.95,0.75,0.3] relative_absolute_error 0.29660493827160517 relative_absolute_error 0.2931790123456794 relative_absolute_error 0.30905202821869504 relative_absolute_error 0.2639880952380955 relative_absolute_error 0.32603174603174634 relative_absolute_error 0.24958774250440935 relative_absolute_error 0.3132142857142859 relative_absolute_error 0.32191578483245176 relative_absolute_error 0.26279982363315724 relative_absolute_error 0.3206547619047623 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 0.20220265878058832 root_mean_squared_error 0.20196978072979715 root_mean_squared_error 0.2158022515463793 root_mean_squared_error 0.18806745659143956 root_mean_squared_error 0.21222781799498994 root_mean_squared_error 0.18792145084269354 root_mean_squared_error 0.20935155858479917 root_mean_squared_error 0.2137499154632446 root_mean_squared_error 0.19152515068766024 root_mean_squared_error 0.211719818526909 root_relative_squared_error 0.6740088626019615 root_relative_squared_error 0.6732326024326575 root_relative_squared_error 0.7193408384879314 root_relative_squared_error 0.6268915219714656 root_relative_squared_error 0.7074260599833002 root_relative_squared_error 0.6264048361423121 root_relative_squared_error 0.6978385286159977 root_relative_squared_error 0.7124997182108157 root_relative_squared_error 0.6384171689588679 root_relative_squared_error 0.7057327284230304 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 2314.440216996445 usercpu_time_millis 2326.178882001841 usercpu_time_millis 2386.0859960004746 usercpu_time_millis 2341.3532939994184 usercpu_time_millis 2340.948623001168 usercpu_time_millis 2347.633405999659 usercpu_time_millis 2360.9400119967177 usercpu_time_millis 2360.8676839976397 usercpu_time_millis 2324.5635139974183 usercpu_time_millis 2350.968129005196 usercpu_time_millis_testing 1.6799819968582597 usercpu_time_millis_testing 1.5218840017041657 usercpu_time_millis_testing 1.6720530002203304 usercpu_time_millis_testing 1.614153999980772 usercpu_time_millis_testing 1.5801650006324053 usercpu_time_millis_testing 1.6153090000443626 usercpu_time_millis_testing 1.5079549993970431 usercpu_time_millis_testing 1.5969099986250512 usercpu_time_millis_testing 1.7145769998023752 usercpu_time_millis_testing 1.625047003471991 usercpu_time_millis_training 2312.760234999587 usercpu_time_millis_training 2324.656998000137 usercpu_time_millis_training 2384.413943000254 usercpu_time_millis_training 2339.7391399994376 usercpu_time_millis_training 2339.3684580005356 usercpu_time_millis_training 2346.0180969996145 usercpu_time_millis_training 2359.4320569973206 usercpu_time_millis_training 2359.2707739990146 usercpu_time_millis_training 2322.848936997616 usercpu_time_millis_training 2349.343082001724