119 30229 Python_3.11.7. Sklearn_1.3.2. NumPy_1.26.3. SciPy_1.11.4. cv {"oml-python:serialized_object": "cv_object", "value": {"name": "sklearn.model_selection._split.StratifiedKFold", "parameters": {"n_splits": "2", "random_state": "62501", "shuffle": "true"}}} 30229 error_score NaN 30229 n_iter 5 30229 n_jobs null 30229 param_distributions {"bootstrap": [true, false], "criterion": ["gini", "entropy"], "max_depth": [3, null], "max_features": [1, 2, 3, 4], "min_samples_leaf": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], "min_samples_split": [2, 3, 4, 5, 6, 7, 8, 9, 10]} 30229 pre_dispatch "2*n_jobs" 30229 random_state 12172 30229 refit true 30229 return_train_score false 30229 scoring null 30229 verbose 0 30229 bootstrap true 30230 ccp_alpha 0.0 30230 class_weight null 30230 criterion "gini" 30230 max_depth null 30230 max_features "sqrt" 30230 max_leaf_nodes null 30230 max_samples null 30230 min_impurity_decrease 0.0 30230 min_samples_leaf 1 30230 min_samples_split 2 30230 min_weight_fraction_leaf 0.0 30230 n_estimators 5 30230 n_jobs null 30230 oob_score false 30230 random_state 33003 30230 verbose 0 30230 warm_start false 30230 openml-python Sklearn_1.3.2. usercpu_time_millis_training 119.14020000000036 wall_clock_time_millis_training 119.1411018371582 usercpu_time_millis_testing 1.1884000000002004 usercpu_time_millis 120.32860000000056 wall_clock_time_millis_testing 1.1906623840332031 wall_clock_time_millis 128.71265411376953 predictive_accuracy 0.7075098814229249