96 14174 Python_3.8.18. Sklearn_1.3.2. NumPy_1.23.5. SciPy_1.10.1. memory null 14174 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "Preprocessing", "step_name": "Preprocessing"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "Classifier", "step_name": "Classifier"}}] 14174 verbose false 14174 n_jobs null 14175 remainder "drop" 14175 sparse_threshold 0.3 14175 transformer_weights null 14175 transformers [{"oml-python:serialized_object": "component_reference", "value": {"key": "categorical", "step_name": "categorical", "argument_1": [0, 3, 4, 5, 6, 8, 9, 11, 12]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "continuous", "step_name": "continuous", "argument_1": [1, 2, 7, 10, 13, 14]}}] 14175 verbose false 14175 verbose_feature_names_out true 14175 categories "auto" 118 drop null 118 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 118 feature_name_combiner "concat" 118 handle_unknown "ignore" 118 max_categories null 118 min_frequency null 118 sparse false 118 sparse_output true 118 add_indicator false 80 copy true 80 fill_value null 80 keep_empty_features false 80 missing_values NaN 80 strategy "median" 80 bootstrap true 44 ccp_alpha 0.0 44 class_weight null 44 criterion "gini" 44 max_depth null 44 max_features "sqrt" 44 max_leaf_nodes null 44 max_samples null 44 min_impurity_decrease 0.0 44 min_samples_leaf 1 44 min_samples_split 2 44 min_weight_fraction_leaf 0.0 44 n_estimators 10 44 n_jobs null 44 oob_score false 44 random_state 43058 44 verbose 0 44 warm_start false 44 openml-python Sklearn_1.3.2. usercpu_time_millis_training 21.461499999993805 wall_clock_time_millis_training 21.46315574645996 usercpu_time_millis_testing 5.6200000000004025 usercpu_time_millis 27.081499999994207 wall_clock_time_millis_testing 5.625009536743164 wall_clock_time_millis 27.088165283203125 predictive_accuracy 0.8898678414096917