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oaioai:HAL:hal-01162980v1

Using the Mean Absolute Percentage Error for Regression Models

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Publication date
22 April 2015
Publisher
HAL CCSD

Abstract

International audienceWe 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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oaioai:HAL:hal-01162980v1
Last time updated on 12/11/2016

This paper was published in HAL-Paris1.

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