10093001 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) 8018112 axis 0 8778 copy true 8778 missing_values "NaN" 8778 strategy "median" 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 3 8783 min_samples_split 2 8783 min_weight_fraction_leaf 0.0 8783 presort false 8783 random_state 58811 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 21106539 description https://api.openml.org/data/download/21106539/description.xml -1 21106540 predictions https://api.openml.org/data/download/21106540/predictions.arff area_under_roc_curve 0.8854590277777777 [0.994933,0.841226,0.937901,0.907965,0.83645,0.921657,0.752571,0.939385,0.970193,0.752308] average_cost 0 f_measure 0.7408491425856732 [0.967901,0.655087,0.869347,0.779904,0.641604,0.82199,0.473815,0.790932,0.938776,0.469136] kappa 0.7111111111111111 kb_relative_information_score 1495.294247827505 mean_absolute_error 0.05296333333333371 mean_prior_absolute_error 0.18000000000000554 number_of_instances 2000 [200,200,200,200,200,200,200,200,200,200] precision 0.7424980203310309 [0.956098,0.650246,0.873737,0.747706,0.643216,0.862637,0.472637,0.796954,0.958333,0.463415] predictive_accuracy 0.74 prior_entropy 3.321928094887362 recall 0.74 [0.98,0.66,0.865,0.815,0.64,0.785,0.475,0.785,0.92,0.475] relative_absolute_error 0.29424074074073375 root_mean_prior_squared_error 0.3000000000000046 root_mean_squared_error 0.21096715120816611 root_relative_squared_error 0.703223837360543 total_cost 0 area_under_roc_curve 0.8964166666666665 [1,0.935694,0.920833,0.946667,0.833472,0.974444,0.734722,0.88625,0.974444,0.757639] area_under_roc_curve 0.8830972222222222 [0.974722,0.874306,0.870139,0.897222,0.750972,0.905278,0.806389,0.964167,0.974306,0.813472] area_under_roc_curve 0.8601805555555555 [1,0.857917,0.924167,0.835833,0.87875,0.894583,0.6225,0.917361,0.997222,0.673472] area_under_roc_curve 0.8987361111111111 [1,0.780556,0.971528,0.973889,0.905972,0.945694,0.723194,0.887222,0.974861,0.824444] area_under_roc_curve 0.8745 [1,0.775833,0.974444,0.912222,0.827361,0.855,0.765278,0.925694,0.969167,0.74] area_under_roc_curve 0.9124861111111109 [1,0.896111,0.99625,0.886667,0.88625,0.946111,0.835972,0.961944,0.997083,0.718472] area_under_roc_curve 0.88275 [0.999722,0.827222,0.872222,0.914306,0.823472,0.911806,0.785833,0.985972,0.999306,0.707639] area_under_roc_curve 0.878013888888889 [0.974861,0.862639,0.920417,0.879167,0.77375,0.9425,0.776944,0.939167,0.894306,0.816389] area_under_roc_curve 0.8946805555555557 [1,0.789167,0.967083,0.969722,0.825972,0.919306,0.753056,0.960833,1,0.761667] area_under_roc_curve 0.873013888888889 [1,0.811111,0.962639,0.863056,0.850139,0.921667,0.726111,0.965139,0.91875,0.711528] 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 0.7459306176636088 [0.97561,0.755556,0.755556,0.842105,0.684211,0.974359,0.428571,0.685714,0.947368,0.410256] f_measure 0.7147737670048557 [0.926829,0.652174,0.833333,0.842105,0.512821,0.648649,0.418605,0.829268,0.947368,0.536585] f_measure 0.7138948998512541 [1,0.666667,0.894737,0.682927,0.731707,0.8,0.311111,0.742857,0.97561,0.333333] f_measure 0.7764285398327953 [1,0.6,0.923077,0.904762,0.638298,0.871795,0.571429,0.756757,0.974359,0.52381] f_measure 0.708275754544189 [0.952381,0.5625,0.95,0.790698,0.6,0.65,0.461538,0.727273,0.926829,0.461538] f_measure 0.7835248761912346 [0.97561,0.8,0.926829,0.744186,0.722222,0.9,0.55814,0.837209,0.95,0.421053] f_measure 0.7261935697921011 [0.923077,0.619048,0.833333,0.75,0.578947,0.8,0.52381,0.883721,0.95,0.4] f_measure 0.728909249231033 [0.95,0.595745,0.842105,0.711111,0.615385,0.9,0.564103,0.705882,0.833333,0.571429] f_measure 0.7488295614303779 [1,0.611111,0.857143,0.808511,0.65,0.8,0.4375,0.790698,1,0.533333] f_measure 0.757388836494428 [0.97561,0.684211,0.883721,0.731707,0.682927,0.864865,0.487805,0.904762,0.871795,0.486486] kappa 0.7166666666666667 kappa 0.6777777777777777 kappa 0.6722222222222222 kappa 0.75 kappa 0.6833333333333333 kappa 0.7611111111111112 kappa 0.6944444444444444 kappa 0.6944444444444444 kappa 0.7277777777777777 kappa 0.7333333333333334 kb_relative_information_score 153.37739780996333 kb_relative_information_score 147.64297027170647 kb_relative_information_score 142.48978661521653 kb_relative_information_score 153.97896769415766 kb_relative_information_score 144.878970338549 kb_relative_information_score 159.54963770843258 kb_relative_information_score 147.3296065409687 kb_relative_information_score 145.6995178260406 kb_relative_information_score 153.00209149300488 kb_relative_information_score 147.34530152949523 mean_absolute_error 0.04905 mean_absolute_error 0.054983333333333315 mean_absolute_error 0.05861666666666661 mean_absolute_error 0.04948333333333333 mean_absolute_error 0.05726666666666664 mean_absolute_error 0.04296666666666668 mean_absolute_error 0.0561 mean_absolute_error 0.0571833333333333 mean_absolute_error 0.04931666666666667 mean_absolute_error 0.054666666666666634 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 0.755363560416192 [0.952381,0.68,0.68,0.888889,0.722222,1,0.409091,0.8,1,0.421053] precision 0.7264909694148153 [0.904762,0.576923,0.9375,0.888889,0.526316,0.705882,0.391304,0.809524,1,0.52381] precision 0.7312323232323233 [1,0.636364,0.944444,0.666667,0.714286,0.933333,0.28,0.866667,0.952381,0.318182] precision 0.7851493260781186 [1,0.6,0.947368,0.863636,0.555556,0.894737,0.666667,0.823529,1,0.5] precision 0.7117018336354721 [0.909091,0.75,0.95,0.73913,0.6,0.65,0.473684,0.666667,0.904762,0.473684] precision 0.7897420634920636 [0.952381,0.933333,0.904762,0.695652,0.8125,0.9,0.521739,0.782609,0.95,0.444444] precision 0.7312975579594573 [0.947368,0.590909,0.9375,0.75,0.611111,0.8,0.5,0.826087,0.95,0.4] precision 0.7448031125794283 [0.95,0.518519,0.888889,0.64,0.631579,0.9,0.578947,0.857143,0.9375,0.545455] precision 0.7595182623334797 [1,0.6875,0.818182,0.703704,0.65,0.933333,0.583333,0.73913,1,0.48] precision 0.7586794429303515 [0.952381,0.722222,0.826087,0.714286,0.666667,0.941176,0.47619,0.863636,0.894737,0.529412] predictive_accuracy 0.745 predictive_accuracy 0.71 predictive_accuracy 0.705 predictive_accuracy 0.775 predictive_accuracy 0.715 predictive_accuracy 0.785 predictive_accuracy 0.725 predictive_accuracy 0.725 predictive_accuracy 0.755 predictive_accuracy 0.76 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 0.745 [1,0.85,0.85,0.8,0.65,0.95,0.45,0.6,0.9,0.4] recall 0.71 [0.95,0.75,0.75,0.8,0.5,0.6,0.45,0.85,0.9,0.55] recall 0.705 [1,0.7,0.85,0.7,0.75,0.7,0.35,0.65,1,0.35] recall 0.775 [1,0.6,0.9,0.95,0.75,0.85,0.5,0.7,0.95,0.55] recall 0.715 [1,0.45,0.95,0.85,0.6,0.65,0.45,0.8,0.95,0.45] recall 0.785 [1,0.7,0.95,0.8,0.65,0.9,0.6,0.9,0.95,0.4] recall 0.725 [0.9,0.65,0.75,0.75,0.55,0.8,0.55,0.95,0.95,0.4] recall 0.725 [0.95,0.7,0.8,0.8,0.6,0.9,0.55,0.6,0.75,0.6] recall 0.755 [1,0.55,0.9,0.95,0.65,0.7,0.35,0.85,1,0.6] recall 0.76 [1,0.65,0.95,0.75,0.7,0.8,0.5,0.95,0.85,0.45] relative_absolute_error 0.2725000000000003 relative_absolute_error 0.3054629629629632 relative_absolute_error 0.3256481481481482 relative_absolute_error 0.2749074074074077 relative_absolute_error 0.31814814814814835 relative_absolute_error 0.23870370370370403 relative_absolute_error 0.311666666666667 relative_absolute_error 0.31768518518518535 relative_absolute_error 0.27398148148148177 relative_absolute_error 0.30370370370370386 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 0.20034414834922878 root_mean_squared_error 0.2143186879392462 root_mean_squared_error 0.22878786875376253 root_mean_squared_error 0.2020588473137907 root_mean_squared_error 0.22097888285233647 root_mean_squared_error 0.1889054731281701 root_mean_squared_error 0.21533049533733536 root_mean_squared_error 0.21907951372351847 root_mean_squared_error 0.20313241439459578 root_mean_squared_error 0.21374439563802988 root_relative_squared_error 0.6678138278307629 root_relative_squared_error 0.7143956264641544 root_relative_squared_error 0.762626229179209 root_relative_squared_error 0.6735294910459693 root_relative_squared_error 0.7365962761744553 root_relative_squared_error 0.629684910427234 root_relative_squared_error 0.7177683177911183 root_relative_squared_error 0.7302650457450619 root_relative_squared_error 0.6771080479819864 root_relative_squared_error 0.7124813187934333 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 194.5319570004358 usercpu_time_millis 178.53521600045497 usercpu_time_millis 177.34938800003874 usercpu_time_millis 192.491470999812 usercpu_time_millis 133.74725499943452 usercpu_time_millis 134.45336799941288 usercpu_time_millis 134.1769220007336 usercpu_time_millis 130.41782100026467 usercpu_time_millis 131.52495700069267 usercpu_time_millis 128.07922399952076 usercpu_time_millis_testing 1.8485280006643734 usercpu_time_millis_testing 1.8094220004059025 usercpu_time_millis_testing 1.8032790003417176 usercpu_time_millis_testing 1.822088999688276 usercpu_time_millis_testing 1.3028109997321735 usercpu_time_millis_testing 1.403600999765331 usercpu_time_millis_testing 1.6594230000919197 usercpu_time_millis_testing 1.3104769996061805 usercpu_time_millis_testing 1.3149450005585095 usercpu_time_millis_testing 1.307386000007682 usercpu_time_millis_training 192.68342899977142 usercpu_time_millis_training 176.72579400004906 usercpu_time_millis_training 175.54610899969703 usercpu_time_millis_training 190.66938200012373 usercpu_time_millis_training 132.44444399970234 usercpu_time_millis_training 133.04976699964755 usercpu_time_millis_training 132.5174990006417 usercpu_time_millis_training 129.1073440006585 usercpu_time_millis_training 130.21001200013416 usercpu_time_millis_training 126.77183799951308