MASE (Mean Absolute Scaled Error)
A forecast’s MAE divided by the training-set error of a naive forecast. Unit-free and comparable across series, and the denominator is easy to get wrong.
A forecast’s MAE divided by the training-set error of a naive forecast. Unit-free and comparable across series, and the denominator is easy to get wrong.