Exploring the grid search results

You will now explore the cv_results_ property of the GridSearchCV object defined in the video. This is a dictionary that we can read into a pandas DataFrame and contains a lot of useful information about the grid search we just undertook.

A reminder of the different column types in this property:

time_columns
params_ columns and the params column
test_score columns for each cv fold including the mean_test_score and std_test_score columns
a rank_test_score column
train_score columns for each cv fold including the mean_train_score and std_train_score columns

We will firstly read the cv_results property into a DataFrame, then extract and explore different elements using pandas loc & iloc attributes.

Read the cv_results_ property of the grid_rf_class GridSearchCV object into a data frame & print the whole thing out to inspect.
Extract & print the column containing cells with a dictionary of the hyperparameters used for that square (row) of the grid search.
Extract & print the row that had the best mean test score.

Take Hint (-30 XP)

Exercise

Exploring the grid search results

Instructions