Lasso Regression, Economic Growth, Macroeconomics, Alpha, Tejapi Data Analysis.
1000))]) large = Lasso_l.fit(df_train, growth_train) growth_pred_l = large.predict(df_valid) large_alpha = list(growth_pred_l) print('大Alpha的MSE:', metrics.mean_squared_error(growth_valid, large_alpha)) Due to the amount of explanatory variable, which is 148, we would consider the effectiveness of