The grid_scores_ is renamed as cv_results_ in the newer version.
So, according to the documentation,your requirements are:
best_index_ : int
The index (of the cv_results_ arrays) which corresponds to the best >
candidate parameter setting.
The dict at search.cv_results_['params'][search.best_index_] gives the >
parameter setting for the best model, that gives the highest mean
score (search.best_score_).
So in your case, you should use:
Best params :- result.cv_results_['params'][result.best_index_] OR result.best_params_
Best mean score :- result.cv_results_['mean_test_score'][result.best_index_] OR result.best_score_
Best std :- result.cv_results_['std_test_score'][result.best_index_]
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