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MAPE Simétrico (sMAPE)×Erro Médio Absoluto (MAE)×
ÁreaAvaliação de modelosAvaliação de modelos
FamíliaMCDMMCDM
Ano de origem19851799
Autor originalJ. Scott ArmstrongPierre-Simon Laplace
TipoSymmetric percentage-based evaluation metricRobust distance-based metric
Fonte seminalArmstrong, J. S. (1985). Long-range forecasting: from crystal ball to computer (2nd ed.). New York: John Wiley & Sons. ISBN: 978-0471082010Laplace, P. S. (1799). Traité de Mécanique Céleste. Paris: J.B.M. Duprat. link ↗
Outros nomessMAPE, SMAPE, symmetric MAPEMAE, L1 error, mean absolute deviation
Relacionados43
ResumoSymmetric Mean Absolute Percentage Error is a refinement of MAPE that addresses its asymmetry by using the average of actual and predicted values as the denominator. Proposed by J. Scott Armstrong and refined by Makridakis (1993) and Hyndman & Koehler (2006), sMAPE treats over- and under-predictions symmetrically.Mean Absolute Error is a robust metric that measures the average absolute magnitude of prediction errors in regression models. Dating back to Pierre-Simon Laplace's work on observational errors (1799), MAE quantifies typical prediction deviation by averaging the absolute differences between observed and predicted values.
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ScholarGateComparar métodos: Symmetric MAPE · Mean Absolute Error. Recuperado em 2026-06-18 de https://scholargate.app/pt/compare