119 30957 Python_3.8.18. Sklearn_0.23.1. NumPy_1.23.5. SciPy_1.10.1. cv 3 30957 error_score NaN 30957 iid "deprecated" 30957 n_jobs null 30957 param_grid {"base_estimator__C": [0.01, 0.1, 10], "base_estimator__gamma": [0.01, 0.1, 10]} 30957 pre_dispatch "2*n_jobs" 30957 refit true 30957 return_train_score false 30957 scoring null 30957 verbose 0 30957 bootstrap true 30958 bootstrap_features false 30958 max_features 1.0 30958 max_samples 1.0 30958 n_estimators 10 30958 n_jobs null 30958 oob_score false 30958 random_state 33003 30958 verbose 0 30958 warm_start false 30958 C 1.0 30959 break_ties false 30959 cache_size 200 30959 class_weight null 30959 coef0 0.0 30959 decision_function_shape "ovr" 30959 degree 3 30959 gamma "scale" 30959 kernel "rbf" 30959 max_iter -1 30959 probability false 30959 random_state 62501 30959 shrinking true 30959 tol 0.001 30959 verbose false 30959 openml-python Sklearn_0.23.1. usercpu_time_millis_training 1385.3194000000003 wall_clock_time_millis_training 1385.3480815887451 usercpu_time_millis_testing 17.93469999999786 usercpu_time_millis 1403.2540999999983 wall_clock_time_millis_testing 17.93694496154785 wall_clock_time_millis 1451.1446952819824 predictive_accuracy 0.6482213438735178