I would like to check in percentage the accuracy of my regression model. I know that normally accuracy is used as a metric for classification. I have evaluated my model based on r-squared and also plotted the y_pred versus y_test.
However, I find it easier to understand the prediction performance in terms of accuracy. Therefore, I would like to do something like this (based on the sklearn, metrics.mean_absolute_percentage_error) :
accuracy = 100 - np.mean(mean_absolute_percentage_error(y_test,y_pred)) print('Accuracy:', round(accuracy, 2), '%.')
Does it make sense, would the result reflect the performance of the regression model based on a percentage of accuracy?