9126 3229 Test Test 6 Supervised Classification 31430 sklearn.pipeline.Pipeline(transform=sklearn.compose._column_transformer.ColumnTransformer(cat=sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder,truncatedsvd=sklearn.decomposition._truncated_svd.TruncatedSVD),cont=sklearn.impute._base.SimpleImputer),estimator=sklearn.ensemble._forest.RandomForestClassifier)(2) 7324 Python_3.8.18. Sklearn_1.3.2. NumPy_1.23.5. SciPy_1.10.1. bootstrap true 31001 ccp_alpha 0.0 31001 class_weight null 31001 criterion "gini" 31001 max_depth 10 31001 max_features "sqrt" 31001 max_leaf_nodes null 31001 max_samples null 31001 min_impurity_decrease 0.0 31001 min_samples_leaf 1 31001 min_samples_split 2 31001 min_weight_fraction_leaf 0.0 31001 n_estimators 50 31001 n_jobs null 31001 oob_score false 31001 random_state 43157 31001 verbose 0 31001 warm_start false 31001 memory null 31430 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "transform", "step_name": "transform"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "estimator", "step_name": "estimator"}}] 31430 verbose false 31430 n_jobs null 31432 remainder "drop" 31432 sparse_threshold 0.3 31432 transformer_weights null 31432 transformers [{"oml-python:serialized_object": "component_reference", "value": {"key": "cat", "step_name": "cat", "argument_1": {"oml-python:serialized_object": "function", "value": "openml.extensions.sklearn.cat"}}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "cont", "step_name": "cont", "argument_1": {"oml-python:serialized_object": "function", "value": "openml.extensions.sklearn.cont"}}}] 31432 verbose false 31432 verbose_feature_names_out true 31432 memory null 31433 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "truncatedsvd", "step_name": "truncatedsvd"}}] 31433 verbose false 31433 categories "auto" 31434 drop null 31434 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 31434 feature_name_combiner "concat" 31434 handle_unknown "ignore" 31434 max_categories null 31434 min_frequency null 31434 sparse false 31434 sparse_output true 31434 algorithm "randomized" 31436 n_components 2 31436 n_iter 5 31436 n_oversamples 10 31436 power_iteration_normalizer "auto" 31436 random_state 51015 31436 tol 0.0 31436 add_indicator false 31437 copy true 31437 fill_value null 31437 keep_empty_features false 31437 missing_values NaN 31437 strategy "median" 31437 openml-python Sklearn_1.3.2. 1 anneal https://www.openml.org/data/download/1666876/phpFsFYVN -1 22551 description https://test.openml.org/data/download/22551/description.xml -1 22552 predictions https://test.openml.org/data/download/22552/predictions.arff area_under_roc_curve 0.9978196469020465 [0.999144,0.995506,0.997725,0.0,1,1] average_cost 0 f_measure 0.9371672809172809 [0.666667,0.727273,0.964286,0.0,1,0.969697] kappa 0.859668693178649 kb_relative_information_score 0.8359978293001734 mean_absolute_error 0.03719987933890885 mean_prior_absolute_error 0.1410223830024713 weighted_recall 0.9425675675675675 [0.5,0.606061,0.995392,0.0,1,0.941176] number_of_instances 296 [4,33,217,0,25,17] precision 0.9422604422604421 [1,0.909091,0.935065,0.0,1,1] predictive_accuracy 0.9425675675675675 prior_entropy 1.3089517057560913 relative_absolute_error 0.2637870566848736 root_mean_prior_squared_error 0.2709125098701948 root_mean_squared_error 0.10991759019451373 root_relative_squared_error 0.40573095073084564 total_cost 0 area_under_roc_curve 0.9978196469020465 [0.999144,0.995506,0.997725,0.0,1,1] average_cost 0 f_measure 0.9371672809172809 [0.666667,0.727273,0.964286,0.0,1,0.969697] kappa 0.859668693178649 kb_relative_information_score 0.8359978293001734 mean_absolute_error 0.03719987933890885 mean_prior_absolute_error 0.1410223830024713 weighted_recall 0.9425675675675675 [0.5,0.606061,0.995392,0.0,1,0.941176] number_of_instances 296 [4,33,217,0,25,17] precision 0.9422604422604421 [1,0.909091,0.935065,0.0,1,1] predictive_accuracy 0.9425675675675675 prior_entropy 1.3089517057560913 relative_absolute_error 0.2637870566848736 root_mean_prior_squared_error 0.2709125098701948 root_mean_squared_error 0.10991759019451373 root_relative_squared_error 0.40573095073084564 total_cost 0 usercpu_time_millis 524.8671000000015 usercpu_time_millis_testing 43.556741999999815 usercpu_time_millis_training 481.31035800000177 wall_clock_time_millis 150.64692497253418 wall_clock_time_millis_training 133.27383995056152 wall_clock_time_millis_testing 17.373085021972656