9954181 6892 Scikit-learn Bot 3573 Supervised Classification 8890 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)(3) 7882094 memory null 8890 n_jobs null 8891 remainder "passthrough" 8891 sparse_threshold 0.3 8891 transformer_weights null 8891 memory null 8892 axis 0 8893 copy true 8893 missing_values "NaN" 8893 strategy "median" 8893 verbose 0 8893 copy true 8894 with_mean true 8894 with_std true 8894 memory null 8895 copy true 8896 fill_value -1 8896 missing_values NaN 8896 strategy "constant" 8896 verbose 0 8896 categorical_features null 8897 categories null 8897 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 8897 handle_unknown "ignore" 8897 n_values null 8897 sparse true 8897 threshold 0.0 8898 criterion "mse" 8899 init null 8899 learning_rate 0.055728645800740155 8899 loss "deviance" 8899 max_depth 8 8899 max_features 0.118850499752583 8899 max_leaf_nodes null 8899 min_impurity_decrease 0.17717271979598448 8899 min_impurity_split null 8899 min_samples_leaf 19 8899 min_samples_split 17 8899 min_weight_fraction_leaf 0.4904213054489292 8899 n_estimators 384 8899 n_iter_no_change 504 8899 presort "auto" 8899 random_state 1105 8899 subsample 0.005841302871362641 8899 tol 0.01796038547897191 8899 validation_fraction 0.5590581577832922 8899 verbose 0 8899 warm_start false 8899 openml-python Sklearn_0.20.2. 554 mnist_784 https://www.openml.org/data/download/52667/mnist_784.arff -1 20828877 description https://api.openml.org/data/download/20828877/description.xml -1 20828878 predictions https://api.openml.org/data/download/20828878/predictions.arff area_under_roc_curve 0.4999224394686915 [0.499871,0.500014,0.5,0.500039,0.500065,0.499817,0.499806,0.499839,0.499862,0.499888] average_cost 0 kappa 0 kb_relative_information_score 441.90906931218143 mean_absolute_error 0.1799217519490464 mean_prior_absolute_error 0.1799414337543242 number_of_instances 70000 [6903,7877,6990,7141,6824,6313,6876,7293,6825,6958] predictive_accuracy 0.11252857142857144 prior_entropy 3.319837620198132 recall 0.11252857142857142 [0,1,0,0,0,0,0,0,0,0] relative_absolute_error 0.9998906210489316 root_mean_prior_squared_error 0.2999511838524139 root_mean_squared_error 0.29997789507836053 root_relative_squared_error 1.0000890519103927 total_cost 0 area_under_roc_curve 0.5 [0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5] area_under_roc_curve 0.5 [0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5] area_under_roc_curve 0.5 [0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5] area_under_roc_curve 0.5 [0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5] area_under_roc_curve 0.5 [0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5] area_under_roc_curve 0.5 [0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5] area_under_roc_curve 0.5 [0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5] area_under_roc_curve 0.5 [0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5] area_under_roc_curve 0.5 [0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5] area_under_roc_curve 0.5 [0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5] 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 kappa 0 kappa 0 kappa 0 kappa 0 kappa 0 kappa 0 kappa 0 kappa 0 kappa 0 kappa 0 kb_relative_information_score 44.36854243051901 kb_relative_information_score 44.35595547228396 kb_relative_information_score 44.343593601774835 kb_relative_information_score 44.343593601774835 kb_relative_information_score 44.343593601774835 kb_relative_information_score 44.3266070137692 kb_relative_information_score 44.3266070137692 kb_relative_information_score 44.30654064712609 kb_relative_information_score 43.583032956874064 kb_relative_information_score 43.611002972474544 mean_absolute_error 0.17992145547343805 mean_absolute_error 0.17992179214097553 mean_absolute_error 0.17992147875771455 mean_absolute_error 0.17992147875771455 mean_absolute_error 0.17992147875771455 mean_absolute_error 0.17992170714964179 mean_absolute_error 0.17992170714964179 mean_absolute_error 0.17992216198612043 mean_absolute_error 0.17992212291422607 mean_absolute_error 0.17992213640345858 mean_prior_absolute_error 0.17994152998551463 mean_prior_absolute_error 0.17994170016528485 mean_prior_absolute_error 0.17994130267104935 mean_prior_absolute_error 0.17994130267104935 mean_prior_absolute_error 0.17994130267104935 mean_prior_absolute_error 0.1799413030791543 mean_prior_absolute_error 0.1799413030791543 mean_prior_absolute_error 0.1799414581590409 mean_prior_absolute_error 0.17994139612708626 mean_prior_absolute_error 0.17994173893525653 number_of_instances 7000 [691,787,699,714,682,631,687,730,683,696] number_of_instances 7000 [691,787,699,714,682,631,688,729,683,696] number_of_instances 7000 [690,788,699,714,682,631,688,729,683,696] number_of_instances 7000 [690,788,699,714,682,631,688,729,683,696] number_of_instances 7000 [690,788,699,714,682,631,688,729,683,696] number_of_instances 7000 [690,788,699,714,683,631,688,729,682,696] number_of_instances 7000 [690,788,699,714,683,631,688,729,682,696] number_of_instances 7000 [690,788,699,715,683,632,687,729,682,695] number_of_instances 7000 [690,788,699,714,683,632,687,730,682,695] number_of_instances 7000 [691,787,699,714,682,632,687,730,682,696] predictive_accuracy 0.11242857142857142 predictive_accuracy 0.11242857142857142 predictive_accuracy 0.11257142857142859 predictive_accuracy 0.11257142857142859 predictive_accuracy 0.11257142857142859 predictive_accuracy 0.11257142857142859 predictive_accuracy 0.11257142857142859 predictive_accuracy 0.11257142857142859 predictive_accuracy 0.11257142857142859 predictive_accuracy 0.11242857142857142 prior_entropy 3.319837620198132 prior_entropy 3.319837620198132 prior_entropy 3.319837620198132 prior_entropy 3.319837620198132 prior_entropy 3.319837620198132 prior_entropy 3.319837620198132 prior_entropy 3.319837620198132 prior_entropy 3.319837620198132 prior_entropy 3.319837620198132 prior_entropy 3.319837620198132 recall 0.11242857142857143 [0,1,0,0,0,0,0,0,0,0] recall 0.11242857142857143 [0,1,0,0,0,0,0,0,0,0] recall 0.11257142857142857 [0,1,0,0,0,0,0,0,0,0] recall 0.11257142857142857 [0,1,0,0,0,0,0,0,0,0] recall 0.11257142857142857 [0,1,0,0,0,0,0,0,0,0] recall 0.11257142857142857 [0,1,0,0,0,0,0,0,0,0] recall 0.11257142857142857 [0,1,0,0,0,0,0,0,0,0] recall 0.11257142857142857 [0,1,0,0,0,0,0,0,0,0] recall 0.11257142857142857 [0,1,0,0,0,0,0,0,0,0] recall 0.11242857142857143 [0,1,0,0,0,0,0,0,0,0] relative_absolute_error 0.999888438694068 relative_absolute_error 0.9998893640312889 relative_absolute_error 0.9998898312225123 relative_absolute_error 0.9998898312225123 relative_absolute_error 0.9998898312225123 relative_absolute_error 0.9998910982127106 relative_absolute_error 0.9998910982127106 relative_absolute_error 0.9998927641627566 relative_absolute_error 0.999892891723222 relative_absolute_error 0.9998910617852538 root_mean_prior_squared_error 0.2999513442637286 root_mean_prior_squared_error 0.29995162794255353 root_mean_prior_squared_error 0.29995096534459187 root_mean_prior_squared_error 0.29995096534459187 root_mean_prior_squared_error 0.29995096534459187 root_mean_prior_squared_error 0.29995096602487803 root_mean_prior_squared_error 0.29995096602487803 root_mean_prior_squared_error 0.29995122453349654 root_mean_prior_squared_error 0.2999511211300758 root_mean_prior_squared_error 0.2999516925695864 root_mean_squared_error 0.29997750155349767 root_mean_squared_error 0.2999780661208981 root_mean_squared_error 0.2999775437768183 root_mean_squared_error 0.2999775437768183 root_mean_squared_error 0.2999775437768183 root_mean_squared_error 0.29997792445828436 root_mean_squared_error 0.29997792445828436 root_mean_squared_error 0.29997870408849664 root_mean_squared_error 0.2999780900627412 root_mean_squared_error 0.29997810870872965 root_relative_squared_error 1.0000872051093261 root_relative_squared_error 1.0000881414730967 root_relative_squared_error 1.0000886092571695 root_relative_squared_error 1.0000886092571695 root_relative_squared_error 1.0000886092571695 root_relative_squared_error 1.000089876134635 root_relative_squared_error 1.000089876134635 root_relative_squared_error 1.0000916134116233 root_relative_squared_error 1.000089911091393 root_relative_squared_error 1.0000880679782698 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 47628.280336997705 usercpu_time_millis 47708.3740280068 usercpu_time_millis 47984.242223988986 usercpu_time_millis 47663.35827100556 usercpu_time_millis 48220.668736990774 usercpu_time_millis 47776.694366009906 usercpu_time_millis 47880.65069199365 usercpu_time_millis 48176.68076901464 usercpu_time_millis 48076.30041000084 usercpu_time_millis 47745.468196997535 usercpu_time_millis_testing 444.6425310015911 usercpu_time_millis_testing 441.33482700272 usercpu_time_millis_testing 447.5057459931122 usercpu_time_millis_testing 445.2748040057486 usercpu_time_millis_testing 442.37245799740776 usercpu_time_millis_testing 445.8552040014183 usercpu_time_millis_testing 446.0166130011203 usercpu_time_millis_testing 443.01939400611445 usercpu_time_millis_testing 442.8118549985811 usercpu_time_millis_testing 449.50216700090095 usercpu_time_millis_training 47183.63780599611 usercpu_time_millis_training 47267.03920100408 usercpu_time_millis_training 47536.73647799587 usercpu_time_millis_training 47218.083466999815 usercpu_time_millis_training 47778.296278993366 usercpu_time_millis_training 47330.83916200849 usercpu_time_millis_training 47434.63407899253 usercpu_time_millis_training 47733.66137500852 usercpu_time_millis_training 47633.48855500226 usercpu_time_millis_training 47295.966029996634