Using the Mean Absolute Percentage Error for Regression Models

نویسندگان

  • Arnaud De Myttenaere
  • Boris Golden
  • Bénédicte Le Grand
  • Fabrice Rossi
چکیده

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.

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عنوان ژورنال:
  • CoRR

دوره abs/1506.04176  شماره 

صفحات  -

تاریخ انتشار 2015