Relative absolute error is a regression evaluation metric that compares a model's total absolute error with the error of a baseline that predicts the average target value. Lower values indicate better performance relative to that baseline.
In regression , an evaluation metric that is the sum of all absolute errors divided by the sum of distances between correct label values and the average of all correct label values.