Gridsearchcv.best_score_ Meaning When Scoring Set To 'accuracy' And Cv

I'm trying to find the best model Neural Network model applied for the classification of breast cancer samples on the well-known Wisconsin Cancer dataset (569 samples, 31 features

Solution 1:

The grid.best_score_ is the average of all cv folds for a single combination of the parameters you specify in the tuned_params.

In order to access other relevant details about the grid searching process, you can look at the grid.cv_results_ attribute.

From the documentation of GridSearchCV:

cv_results_ : dict of numpy (masked) ndarrays

A dict with keys as column headers and values as columns, 
that can be imported into a pandas DataFrame

It contains keys like 'split0_test_score', 'split1_test_score' , 'mean_test_score', 'std_test_score', 'rank_test_score', 'split0_train_score', 'split1_train_score', 'mean_train_score', etc, which gives additional information about the whole execution.