Research work · 2015
Using the Mean Absolute Percentage Error for Regression Models
Arnaud De Myttenaere, Boris Golden, Bénédicte Le Grand, Fabrice Rossi
arXiv (Cornell University)
Abstract
We study in this paper the consequences of using the Mean Absolute Percentage Error (MAPE) as a measure of quality for regression models. We show that finding the best model under the MAPE is equivalent to doing weighted Mean Absolute Error (MAE) regression. We show that universal consistency of Empirical Risk Minimization remains possible using the MAPE instead of the MAE.