2a901c961b51294530628eabca4820384684a59a,auto_ml/predictor.py,Predictor,_print_ml_analytics_results_regression,#Predictor#,375

Before Change

    def _print_ml_analytics_results_regression(self):
        print("\n\nHere are the results from our " + self.trained_pipeline.named_steps["final_model"].model_name)

        if self.trained_pipeline.named_steps.get("feature_selection", False):

            selected_indices = self.trained_pipeline.named_steps["feature_selection"].support_mask
            feature_names_before_selection = self.trained_pipeline.named_steps["dv"].get_feature_names()
            trained_feature_names = [name for idx, name in enumerate(feature_names_before_selection) if selected_indices[idx]]

        else:
            trained_feature_names = self.trained_pipeline.named_steps["dv"].get_feature_names()

        if self.type_of_estimator == "classifier":
            trained_coefficients = self.trained_pipeline.named_steps["final_model"].model.coef_[0]
        else:
            trained_coefficients = self.trained_pipeline.named_steps["final_model"].model.coef_

After Change

    def _print_ml_analytics_results_regression(self):
        print("\n\nHere are the results from our " + self.trained_pipeline.named_steps["final_model"].model_name)

        trained_feature_names = self._get_trained_feature_names()

        if self.type_of_estimator == "classifier":
            trained_coefficients = self.trained_pipeline.named_steps["final_model"].model.coef_[0]
        else:

Instances