090b20a6dc31cb152505523e5f48c87f6142278c,auto_ml/predictor.py,Predictor,train,#Predictor#,213

Before Change

        subpredictor_column_descriptions, subpredictor_type_of_estimator = self._make_subpredictor_column_descriptions(self.column_descriptions)

        subpredictor1 = Predictor(type_of_estimator=subpredictor_type_of_estimator, column_descriptions=subpredictor_column_descriptions)

        // NOTE that we will be mutating the input X here by stripping off the y values.
        subpredictor1.train(raw_training_data=X, perform_feature_selection=True, X_test=X_test, y_test=y_test, ml_for_analytics=True, compute_power=1, take_log_of_y=False, add_cluster_prediction=False, model_names=["XGBRegressor"])
        print("made it past subpredictor1")

        if self.take_log_of_y:
            y = [math.log(val) for val in y]

After Change

        if self.subpredictor_count > 0:
            subpredictor_column_descriptions, subpredictor_type_of_estimator = self._make_subpredictor_column_descriptions(self.column_descriptions)

            subpredictor1 = Predictor(type_of_estimator=subpredictor_type_of_estimator, column_descriptions=subpredictor_column_descriptions)
            // print(X[:3])
            // NOTE that we will be mutating the input X here by stripping off the y values.
            subpredictor1.train(raw_training_data=X, perform_feature_selection=True, X_test=X_test, y_test=y_test, ml_for_analytics=True, compute_power=1, take_log_of_y=False, add_cluster_prediction=False, model_names=["XGBRegressor"])
        print("made it past subpredictor1")

        if self.take_log_of_y:
            y = [math.log(val) for val in y]

Instances