Machine Learning Model Evaluation – Regression

After building a number of different regression models, there is a wealth of criteria by which they can be evaluated and compared.

Root Mean Squared Error

RMSE is a popular formula to measure the error rate of a regression model. However, it can only be compared between models whose errors are measured in the same units.

Relative Squared Error

Unlike RMSE, the relative squared error (RSE) can be compared between models whose errors are measured in the different units.

Mean Absolute Error

The mean absolute error (MAE) has the same unit as the original data, and it can only be compared between models whose errors are measured in the same units. It is usually similar in magnitude to RMSE, but slightly smaller.

Relative Absolute Error

Like RSE , the relative absolute error (RAE) can be compared between models whose errors are measured in the different units.

Reference

https://www.saedsayad.com/model_evaluation.htm