from sklearn.ensemble import RandomForestClassifier

print(iris.feature_names)
for max_depth in [2, 5, 7]:
    rf_tree = RandomForestClassifier(n_estimators = 150, 
                                 max_depth = max_depth, random_state = 10)
    rf_tree.fit(X,y)
    print(rf_tree.feature_importances_)
