Marketing Analytics: Predicting Customer Churn in Python
Mark Peterson
Director of Data Science, Infoblox
random_forest = RandomForestClassifier()
random_forest.fit(X_train, y_train)
random_forest.feature_importances_
array([0.02716028 0.02960326 0.13820047 0.0700711 0.03798189 0.04722036
0.13258838 0.07066312 0.02333901 0.02982636 0.13711014 0.0300661
0.06351097 0.02860241 0.0382932 0.05200864 0.04375429])
Marketing Analytics: Predicting Customer Churn in Python