gradientboostingmodel.py 文件源码

def after_test(self):
        scores_test=[]
        scores_train=[]
        scores_test_mse = []
        scores_train_mse = []
        for i, y_pred in enumerate(self.clf.staged_predict(self.X_test)):
            scores_test.append(mean_absolute_percentage_error(self.y_test, y_pred))
            scores_test_mse.append(mean_squared_error(self.y_test, y_pred))

        for i, y_pred in enumerate(self.clf.staged_predict(self.X_train)):
            scores_train.append(mean_absolute_percentage_error(self.y_train, y_pred))
            scores_train_mse.append(mean_squared_error(self.y_train, y_pred))

        pd.DataFrame({'scores_train': scores_train, 'scores_test': scores_test,'scores_train_mse': scores_train_mse, 'scores_test_mse': scores_test_mse}).to_csv('temp/trend.csv')
        df = pd.DataFrame({'scores_train': scores_train, 'scores_test': scores_test})
        print "Test set MAPE minimum: {}".format(np.array(scores_test).min())
#         df.plot()
#         plt.show()
        return