CODEWITHSUNDEEP
machine-learningscikit-learngridsearchcv
Dhvanesh Shah
Dhvanesh Shah

Reputation: 37

GridSearchCV and its feature importance

In gridsearchCV, when I fit like something as follows:

forest_reg = RandomForestRegressor()
grid_search = GridSearchCV(forest_reg, param_grid,cv=5,scoring = 'neg_mean_squared_error')
grid_search.fit(X_train,y_train)

and after that, when I execute this, 

GridSearch.best_estimator_.feature_importances_

it gives an array of values so my question is what values does GridSearch.best_estimator_.feature_importances_ this line return??

Upvotes: 1

Views: 2765

Answers (1)

Gustavo Fonseca
Gustavo Fonseca

Reputation: 651

In your case, GridSearch.best_estimator_.feature_importances_ returns a RandomForestRegressor object.

Therefore, according to RandomForestRegressor documentation:

feature_importances_ : array of shape = [n_features] Return the feature importances (the higher, the more important the feature).

In other words, it returns the most important features according to your training set X_train. Each element of feature_importances_ corresponds to one feature of X_train (e.g: first element of feature_importances_ refers to the first feature/column of X_train).

The higher the value of an element in feature_importances_, the more important is the feature in X_train.

Upvotes: 1

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