9910380 6892 Scikit-learn Bot 14 Supervised Classification 8834 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,gradientboostingclassifier=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier)(1) 7839773 memory null 8834 n_jobs null 8835 remainder "passthrough" 8835 sparse_threshold 0.3 8835 transformer_weights null 8835 memory null 8836 axis 0 8837 copy true 8837 missing_values "NaN" 8837 strategy "mean" 8837 verbose 0 8837 copy true 8838 with_mean true 8838 with_std true 8838 memory null 8839 copy true 8840 fill_value -1 8840 missing_values NaN 8840 strategy "constant" 8840 verbose 0 8840 categorical_features null 8841 categories null 8841 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 8841 handle_unknown "ignore" 8841 n_values null 8841 sparse true 8841 threshold 0.0 8842 criterion "friedman_mse" 8843 init null 8843 learning_rate 0.020282769978940487 8843 loss "deviance" 8843 max_depth 7 8843 max_features 0.7836036941416182 8843 max_leaf_nodes null 8843 min_impurity_decrease 0.5697604065266533 8843 min_impurity_split null 8843 min_samples_leaf 14 8843 min_samples_split 6 8843 min_weight_fraction_leaf 0.05756936800261436 8843 n_estimators 310 8843 n_iter_no_change 332 8843 presort "auto" 8843 random_state 32111 8843 subsample 0.39377183130047166 8843 tol 2.0241430669508063e-05 8843 validation_fraction 0.44322787711359146 8843 verbose 0 8843 warm_start false 8843 openml-python Sklearn_0.20.1. 14 mfeat-fourier https://www.openml.org/data/download/14/dataset_14_mfeat-fourier.arff -1 20741216 description https://api.openml.org/data/download/20741216/description.xml -1 20741217 predictions https://api.openml.org/data/download/20741217/predictions.arff area_under_roc_curve 0.970903611111111 [0.998783,0.9332,0.991494,0.977042,0.961078,0.988289,0.944953,0.983106,0.993492,0.9376] average_cost 0 f_measure 0.778600144650901 [0.965517,0.717557,0.887179,0.819095,0.747423,0.859296,0.502538,0.839907,0.945,0.502488] kappa 0.755 kb_relative_information_score 1434.0104677773822 mean_absolute_error 0.07662137978837867 mean_prior_absolute_error 0.18000000000000554 number_of_instances 2000 [200,200,200,200,200,200,200,200,200,200] precision 0.7789556919169282 [0.951456,0.73057,0.910526,0.823232,0.771277,0.863636,0.510309,0.78355,0.945,0.5] predictive_accuracy 0.7795000000000001 prior_entropy 3.321928094887362 recall 0.7795 [0.98,0.705,0.865,0.815,0.725,0.855,0.495,0.905,0.945,0.505] relative_absolute_error 0.42567433215764616 root_mean_prior_squared_error 0.3000000000000046 root_mean_squared_error 0.17790080044286802 root_relative_squared_error 0.5930026681428844 total_cost 0 area_under_roc_curve 0.9683888888888889 [0.993056,0.913056,0.990556,0.966389,0.967222,0.999167,0.923333,0.98,0.9975,0.953611] area_under_roc_curve 0.9641111111111113 [0.999722,0.925278,0.991944,0.961667,0.941944,0.985556,0.956667,0.945556,0.985556,0.947222] area_under_roc_curve 0.9704444444444446 [0.999722,0.928056,0.994444,0.9775,0.950278,0.984444,0.930833,0.981944,1,0.957222] area_under_roc_curve 0.9713055555555558 [0.999722,0.906667,0.997778,0.9875,0.984167,0.976667,0.968056,0.983056,0.984167,0.925278] area_under_roc_curve 0.9672777777777776 [1,0.910278,0.992222,0.964722,0.944444,0.993056,0.956667,0.981389,1,0.93] area_under_roc_curve 0.9729166666666668 [0.999722,0.92,0.995556,0.9925,0.975833,0.986944,0.941944,0.992222,0.998889,0.925556] area_under_roc_curve 0.976722222222222 [0.997778,0.959167,0.983611,0.980556,0.975,0.979444,0.966111,0.988333,0.998333,0.938889] area_under_roc_curve 0.9771944444444445 [1,0.946944,0.987222,0.986111,0.959722,0.994167,0.9475,0.995278,0.998333,0.956667] area_under_roc_curve 0.9782222222222222 [1,0.948056,0.999167,0.994167,0.975278,0.990278,0.946944,0.994722,1,0.933611] area_under_roc_curve 0.9681111111111111 [1,0.9825,0.989444,0.966667,0.946111,0.998333,0.9175,0.988889,0.977222,0.914444] 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 0.75547222769071 [0.95,0.697674,0.85,0.842105,0.727273,0.974359,0.465116,0.789474,0.883721,0.375] f_measure 0.7599149887339876 [0.97561,0.682927,0.833333,0.829268,0.631579,0.780488,0.578947,0.727273,0.974359,0.585366] f_measure 0.7908402731468975 [0.974359,0.75,0.864865,0.731707,0.790698,0.842105,0.545455,0.878049,0.97561,0.555556] f_measure 0.794782516014865 [0.97561,0.685714,0.947368,0.857143,0.755556,0.789474,0.555556,0.829268,0.974359,0.577778] f_measure 0.7862801926784654 [1,0.631579,0.923077,0.780488,0.705882,0.863636,0.555556,0.844444,1,0.55814] f_measure 0.7894746716697935 [0.97561,0.777778,0.9,0.871795,0.820513,0.857143,0.47619,0.888889,0.926829,0.4] f_measure 0.7917896026505169 [0.9,0.75,0.894737,0.829268,0.787879,0.857143,0.564103,0.869565,0.952381,0.512821] f_measure 0.7819702615173852 [0.930233,0.714286,0.871795,0.8,0.842105,0.864865,0.5,0.883721,0.888889,0.52381] f_measure 0.781519973292158 [1,0.648649,0.97561,0.9,0.666667,0.85,0.4,0.863636,1,0.510638] f_measure 0.7474192998711612 [0.97561,0.829268,0.809524,0.742857,0.736842,0.918919,0.390244,0.818182,0.871795,0.380952] kappa 0.7333333333333334 kappa 0.7333333333333334 kappa 0.7666666666666667 kappa 0.7722222222222223 kappa 0.7666666666666667 kappa 0.7722222222222223 kappa 0.7722222222222223 kappa 0.7555555555555555 kappa 0.7611111111111112 kappa 0.7166666666666667 kb_relative_information_score 142.26867297919367 kb_relative_information_score 141.33823906825353 kb_relative_information_score 142.80002931006516 kb_relative_information_score 144.3393588123791 kb_relative_information_score 142.3229482236757 kb_relative_information_score 145.48093601628025 kb_relative_information_score 144.2938388602709 kb_relative_information_score 145.54943681911374 kb_relative_information_score 146.6471475258072 kb_relative_information_score 138.9698601623452 mean_absolute_error 0.07826509147358585 mean_absolute_error 0.07702105843291637 mean_absolute_error 0.07768041133140435 mean_absolute_error 0.07502375836267111 mean_absolute_error 0.07744015695315343 mean_absolute_error 0.07500170492996229 mean_absolute_error 0.07636430218340017 mean_absolute_error 0.07430260318945325 mean_absolute_error 0.07488927599164344 mean_absolute_error 0.08022543503559774 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 0.7601932367149757 [0.95,0.652174,0.85,0.888889,0.666667,1,0.434783,0.833333,0.826087,0.5] precision 0.7643849206349206 [0.952381,0.666667,0.9375,0.809524,0.666667,0.761905,0.611111,0.666667,1,0.571429] precision 0.7968005318069257 [1,0.75,0.941176,0.714286,0.73913,0.888889,0.5,0.857143,0.952381,0.625] precision 0.8038419913419914 [0.952381,0.8,1,0.818182,0.68,0.833333,0.625,0.809524,1,0.52] precision 0.7931488503868366 [1,0.666667,0.947368,0.761905,0.857143,0.791667,0.625,0.76,1,0.521739] precision 0.7908378901799955 [0.952381,0.875,0.9,0.894737,0.842105,0.818182,0.454545,0.8,0.904762,0.466667] precision 0.8005734908366486 [0.9,0.75,0.944444,0.809524,1,0.818182,0.578947,0.769231,0.909091,0.526316] precision 0.7902272557313611 [0.869565,0.681818,0.894737,0.8,0.888889,0.941176,0.5,0.826087,1,0.5] precision 0.7861041083099906 [1,0.705882,0.952381,0.9,0.75,0.85,0.466667,0.791667,1,0.444444] precision 0.7568402065770488 [0.952381,0.809524,0.772727,0.866667,0.777778,1,0.380952,0.75,0.894737,0.363636] predictive_accuracy 0.76 predictive_accuracy 0.76 predictive_accuracy 0.79 predictive_accuracy 0.795 predictive_accuracy 0.79 predictive_accuracy 0.795 predictive_accuracy 0.795 predictive_accuracy 0.78 predictive_accuracy 0.785 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 0.76 [0.95,0.75,0.85,0.8,0.8,0.95,0.5,0.75,0.95,0.3] recall 0.76 [1,0.7,0.75,0.85,0.6,0.8,0.55,0.8,0.95,0.6] recall 0.79 [0.95,0.75,0.8,0.75,0.85,0.8,0.6,0.9,1,0.5] recall 0.795 [1,0.6,0.9,0.9,0.85,0.75,0.5,0.85,0.95,0.65] recall 0.79 [1,0.6,0.9,0.8,0.6,0.95,0.5,0.95,1,0.6] recall 0.795 [1,0.7,0.9,0.85,0.8,0.9,0.5,1,0.95,0.35] recall 0.795 [0.9,0.75,0.85,0.85,0.65,0.9,0.55,1,1,0.5] recall 0.78 [1,0.75,0.85,0.8,0.8,0.8,0.5,0.95,0.8,0.55] recall 0.785 [1,0.6,1,0.9,0.6,0.85,0.35,0.95,1,0.6] recall 0.745 [1,0.85,0.85,0.65,0.7,0.85,0.4,0.9,0.85,0.4] relative_absolute_error 0.4348060637421441 relative_absolute_error 0.4278947690717581 relative_absolute_error 0.43155784073002473 relative_absolute_error 0.4167986575703955 relative_absolute_error 0.43022309418418614 relative_absolute_error 0.41667613849979096 relative_absolute_error 0.4242461232411125 relative_absolute_error 0.41279223994140746 relative_absolute_error 0.41605153328690847 relative_absolute_error 0.4456968613088768 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 0.18171372607140748 root_mean_squared_error 0.18613782802992102 root_mean_squared_error 0.17730975388515344 root_mean_squared_error 0.1753570182763392 root_mean_squared_error 0.18097843543302022 root_mean_squared_error 0.17362756566544407 root_mean_squared_error 0.1755575745862961 root_mean_squared_error 0.17288075093405392 root_mean_squared_error 0.1707920021214874 root_mean_squared_error 0.1839921094954762 root_relative_squared_error 0.6057124202380253 root_relative_squared_error 0.6204594267664038 root_relative_squared_error 0.5910325129505118 root_relative_squared_error 0.5845233942544644 root_relative_squared_error 0.6032614514434012 root_relative_squared_error 0.5787585522181473 root_relative_squared_error 0.585191915287654 root_relative_squared_error 0.5762691697801801 root_relative_squared_error 0.5693066737382917 root_relative_squared_error 0.6133070316515876 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 6966.80530699814 usercpu_time_millis 6916.125051000563 usercpu_time_millis 6913.909523002076 usercpu_time_millis 6931.146793001972 usercpu_time_millis 6963.061682003172 usercpu_time_millis 6945.2913039967825 usercpu_time_millis 6925.327732998994 usercpu_time_millis 6924.392445002013 usercpu_time_millis 6938.045981001778 usercpu_time_millis 6935.729298998922 usercpu_time_millis_testing 9.49982999736676 usercpu_time_millis_testing 10.02491200051736 usercpu_time_millis_testing 9.373696000693599 usercpu_time_millis_testing 9.206144000927452 usercpu_time_millis_testing 9.449643002881203 usercpu_time_millis_testing 9.965763998479815 usercpu_time_millis_testing 9.819582999625709 usercpu_time_millis_testing 9.3917699996382 usercpu_time_millis_testing 9.48028300263104 usercpu_time_millis_testing 9.285678999731317 usercpu_time_millis_training 6957.305477000773 usercpu_time_millis_training 6906.100139000046 usercpu_time_millis_training 6904.535827001382 usercpu_time_millis_training 6921.940649001044 usercpu_time_millis_training 6953.612039000291 usercpu_time_millis_training 6935.325539998303 usercpu_time_millis_training 6915.5081499993685 usercpu_time_millis_training 6915.000675002375 usercpu_time_millis_training 6928.565697999147 usercpu_time_millis_training 6926.443619999191