Mean Absolute Error
Mean Absolute Error (MAE) is a metric for assessing regression predictions. Simply take the average of the absolute error between all labels and predictions in the test set:
Step-by-step:
- Calculate error vector as labels - predictions
- Take the absolute values of the errors
- Take the mean of all values.
It's also known as L1 Loss because it takes the L1 Norm of the error vector
An alternative to Root Mean-Squared Error.