tiaplagata · November 15, 2020 23:49
diff --git a/basic_pipe_abilities.py b/basic_pipe_abilities.py
 # First fit the pipeline to your training data, like you would with an estimator
 basic_pipe.fit(X_train, y_train)

 # Next you can reference the pipeline object in the same way as an estimator
 score = basic_pipe.score(X_test, y_test)

 test_preds = basic_pipe.predict(X_test)

 # You can even reference your feature importances for certain types of estimators
 # To do this, index the estimator step, and the method within the tuple to access all the RandomForestClassifier attributes
 basic_pipe[1][1].feature_importances_
	# First fit the pipeline to your training data, like you would with an estimator
	basic_pipe.fit(X_train, y_train)

	# Next you can reference the pipeline object in the same way as an estimator
	score = basic_pipe.score(X_test, y_test)

	test_preds = basic_pipe.predict(X_test)

	# You can even reference your feature importances for certain types of estimators
	# To do this, index the estimator step, and the method within the tuple to access all the RandomForestClassifier attributes
	basic_pipe[1][1].feature_importances_