10220504 1 Jan van Rijn 3543 Supervised Classification 9666 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)(4) 8145936 copy true 9559 fill_value -1 9559 missing_values NaN 9559 strategy "constant" 9559 verbose 0 9559 n_jobs null 9606 remainder "passthrough" 9606 sparse_threshold 0.3 9606 transformer_weights null 9606 transformers [{"oml-python:serialized_object": "component_reference", "value": {"key": "numeric", "step_name": "numeric", "argument_1": [1, 3]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "nominal", "step_name": "nominal", "argument_1": [0, 2, 4]}}] 9606 memory null 9607 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "imputer", "step_name": "imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}] 9607 axis 0 9608 copy true 9608 missing_values "NaN" 9608 strategy "most_frequent" 9608 verbose 0 9608 copy true 9609 with_mean true 9609 with_std true 9609 memory null 9610 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}] 9610 categorical_features null 9611 categories null 9611 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 9611 handle_unknown "ignore" 9611 n_values null 9611 sparse true 9611 threshold 0.0 9612 memory null 9666 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "variancethreshold", "step_name": "variancethreshold"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "gradientboostingclassifier", "step_name": "gradientboostingclassifier"}}] 9666 criterion "mae" 9667 init null 9667 learning_rate 0.00021320720265849375 9667 loss "deviance" 9667 max_depth 24 9667 max_features 0.4923618367076916 9667 max_leaf_nodes null 9667 min_impurity_decrease 0.2403327170864803 9667 min_impurity_split null 9667 min_samples_leaf 17 9667 min_samples_split 11 9667 min_weight_fraction_leaf 0.45447729897511463 9667 n_estimators 722 9667 n_iter_no_change 85 9667 presort "auto" 9667 random_state 43747 9667 subsample 0.14327859206196314 9667 tol 3.359711996228305e-05 9667 validation_fraction 0.49612817069727555 9667 verbose 0 9667 warm_start false 9667 openml-python Sklearn_0.20.3. 451 irish https://www.openml.org/data/download/52563/irish.arff -1 21361924 description https://api.openml.org/data/download/21361924/description.xml -1 21361925 predictions https://api.openml.org/data/download/21361925/predictions.arff area_under_roc_curve 0.5 [0.5,0.5] average_cost 0 kappa 0 kb_relative_information_score 2.1986841465863223 mean_absolute_error 0.492051362326885 mean_prior_absolute_error 0.49375298804780854 number_of_instances 500 [278,222] predictive_accuracy 0.556 prior_entropy 0.9910046621528215 recall 0.556 [1,0] relative_absolute_error 0.9965536902821563 root_mean_prior_squared_error 0.49685415342632255 root_mean_squared_error 0.49707957137461684 root_relative_squared_error 1.0004536903772259 total_cost 0 area_under_roc_curve 0.5 [0.5,0.5] area_under_roc_curve 0.5 [0.5,0.5] area_under_roc_curve 0.5 [0.5,0.5] area_under_roc_curve 0.5 [0.5,0.5] area_under_roc_curve 0.5 [0.5,0.5] area_under_roc_curve 0.5 [0.5,0.5] area_under_roc_curve 0.5 [0.5,0.5] area_under_roc_curve 0.5 [0.5,0.5] area_under_roc_curve 0.5 [0.5,0.5] area_under_roc_curve 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 0.23557330141996252 kb_relative_information_score 0.23557330141996252 kb_relative_information_score 0.23557330141996252 kb_relative_information_score 0.23557330141996252 kb_relative_information_score 0.23557330141996252 kb_relative_information_score 0.23557330141996252 kb_relative_information_score 0.23557330141996252 kb_relative_information_score 0.23557330141996252 kb_relative_information_score 0.15704886761330827 kb_relative_information_score 0.15704886761330827 mean_absolute_error 0.4914836024930907 mean_absolute_error 0.4914836024930907 mean_absolute_error 0.4914836024930907 mean_absolute_error 0.4914836024930907 mean_absolute_error 0.4914836024930907 mean_absolute_error 0.4914836024930907 mean_absolute_error 0.4914836024930907 mean_absolute_error 0.4914836024930907 mean_absolute_error 0.4943224016620605 mean_absolute_error 0.4943224016620605 mean_prior_absolute_error 0.49330677290836705 mean_prior_absolute_error 0.49330677290836705 mean_prior_absolute_error 0.49330677290836705 mean_prior_absolute_error 0.49330677290836705 mean_prior_absolute_error 0.49330677290836705 mean_prior_absolute_error 0.49330677290836705 mean_prior_absolute_error 0.49330677290836705 mean_prior_absolute_error 0.49330677290836705 mean_prior_absolute_error 0.49553784860557826 mean_prior_absolute_error 0.49553784860557826 number_of_instances 50 [28,22] number_of_instances 50 [28,22] number_of_instances 50 [28,22] number_of_instances 50 [28,22] number_of_instances 50 [28,22] number_of_instances 50 [28,22] number_of_instances 50 [28,22] number_of_instances 50 [28,22] number_of_instances 50 [27,23] number_of_instances 50 [27,23] predictive_accuracy 0.56 predictive_accuracy 0.56 predictive_accuracy 0.56 predictive_accuracy 0.56 predictive_accuracy 0.56 predictive_accuracy 0.56 predictive_accuracy 0.56 predictive_accuracy 0.56 predictive_accuracy 0.54 predictive_accuracy 0.54 prior_entropy 0.9910046621528215 prior_entropy 0.9910046621528215 prior_entropy 0.9910046621528215 prior_entropy 0.9910046621528215 prior_entropy 0.9910046621528215 prior_entropy 0.9910046621528215 prior_entropy 0.9910046621528215 prior_entropy 0.9910046621528215 prior_entropy 0.9910046621528215 prior_entropy 0.9910046621528215 recall 0.56 [1,0] recall 0.56 [1,0] recall 0.56 [1,0] recall 0.56 [1,0] recall 0.56 [1,0] recall 0.56 [1,0] recall 0.56 [1,0] recall 0.56 [1,0] recall 0.54 [1,0] recall 0.54 [1,0] relative_absolute_error 0.9963041853155035 relative_absolute_error 0.9963041853155035 relative_absolute_error 0.9963041853155035 relative_absolute_error 0.9963041853155035 relative_absolute_error 0.9963041853155035 relative_absolute_error 0.9963041853155035 relative_absolute_error 0.9963041853155035 relative_absolute_error 0.9963041853155035 relative_absolute_error 0.9975472167324091 relative_absolute_error 0.9975472167324091 root_mean_prior_squared_error 0.49640490996518694 root_mean_prior_squared_error 0.49640490996518694 root_mean_prior_squared_error 0.49640490996518694 root_mean_prior_squared_error 0.49640490996518694 root_mean_prior_squared_error 0.49640490996518694 root_mean_prior_squared_error 0.49640490996518694 root_mean_prior_squared_error 0.49640490996518694 root_mean_prior_squared_error 0.49640490996518694 root_mean_prior_squared_error 0.49864707994207336 root_mean_prior_squared_error 0.49864707994207336 root_mean_squared_error 0.4965081474096677 root_mean_squared_error 0.4965081474096677 root_mean_squared_error 0.4965081474096677 root_mean_squared_error 0.4965081474096677 root_mean_squared_error 0.4965081474096677 root_mean_squared_error 0.4965081474096677 root_mean_squared_error 0.4965081474096677 root_mean_squared_error 0.4965081474096677 root_mean_squared_error 0.4993587283838644 root_mean_squared_error 0.4993587283838644 root_relative_squared_error 1.0002079702323816 root_relative_squared_error 1.0002079702323816 root_relative_squared_error 1.0002079702323816 root_relative_squared_error 1.0002079702323816 root_relative_squared_error 1.0002079702323816 root_relative_squared_error 1.0002079702323816 root_relative_squared_error 1.0002079702323816 root_relative_squared_error 1.0002079702323816 root_relative_squared_error 1.0014271585464287 root_relative_squared_error 1.0014271585464287 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 74.25828800114687 usercpu_time_millis 67.49856300302781 usercpu_time_millis 66.97595099831233 usercpu_time_millis 66.90681700274581 usercpu_time_millis 67.94973899741308 usercpu_time_millis 67.62125699970056 usercpu_time_millis 66.96634699983406 usercpu_time_millis 62.99470100202598 usercpu_time_millis 62.365608999243705 usercpu_time_millis 62.78512700009742 usercpu_time_millis_testing 3.1922410016704816 usercpu_time_millis_testing 3.103350001765648 usercpu_time_millis_testing 2.9235209985927213 usercpu_time_millis_testing 2.9186370011302643 usercpu_time_millis_testing 3.1795129980309866 usercpu_time_millis_testing 2.9355549995671026 usercpu_time_millis_testing 2.9297170003701467 usercpu_time_millis_testing 2.7031120007450227 usercpu_time_millis_testing 2.9817030008416623 usercpu_time_millis_testing 2.962262002256466 usercpu_time_millis_training 71.06604699947638 usercpu_time_millis_training 64.39521300126216 usercpu_time_millis_training 64.0524299997196 usercpu_time_millis_training 63.98818000161555 usercpu_time_millis_training 64.77022599938209 usercpu_time_millis_training 64.68570200013346 usercpu_time_millis_training 64.03662999946391 usercpu_time_millis_training 60.291589001280954 usercpu_time_millis_training 59.38390599840204 usercpu_time_millis_training 59.82286499784095