Added missing plot

code/machine_learning_models/decision_tree.py

@@ -96,7 +96,7 @@ train(dtc2)
 features = pd.DataFrame(dtc2.feature_importances_,
                         index= X.columns,
                         columns=['Importance']).sort_values(by='Importance', ascending=False)
-plot_features(features, model_name=model_name)
+plot_features(features, model_name=model_name + "2")
 
 def predict(prediction_input):
     if len(prediction_input) == 0: