Feature Importance from a GridSearchCV

Question

I created a GridSearchCV for a Random Forest Regressor. Now i want to check the feature importance. I searched around and I found this

rf_gridsearch.best_estimator_.named_steps.feature_importances_

This already works, but my trainingdata are huge, 669 Attributes therefore i need the attributenames so I found this code

rf_gridsearch.best_estimator_.named_steps["step_name"].feature_importances_

But I dont know that the "named_steps["step_name"]" are.

I tried something like this

named_steps = X_train.columns

But this doesnt work. Could somebody explain me what "named_steps["step_name"]" is? Thank you and sorry for my noob questions

Answer 1

I think that you need just

feature_importances = rf_gridsearch.best_estimator_.feature_importances_

This provides the feature importances for all the attribures in your dataset. For more information on this as well as other options, you may also refer to Scikit-learn official documentation.