Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Erreur Absolue Moyenne Normalisée (MASE)× | MAPE symétrique (sMAPE)× | |
|---|---|---|
| Domaine | Évaluation de modèles | Évaluation de modèles |
| Famille | MCDM | MCDM |
| Année d'origine≠ | 2006 | 1985 |
| Auteur d'origine≠ | Rob J. Hyndman and Anne B. Koehler | J. Scott Armstrong |
| Type≠ | Scale-independent baseline comparison metric | Symmetric percentage-based evaluation metric |
| Source fondatrice≠ | Hyndman, R. J., & Koehler, A. B. (2006). Another look at measures of forecast accuracy. International Journal of Forecasting, 22(4), 679-688. DOI ↗ | Armstrong, J. S. (1985). Long-range forecasting: from crystal ball to computer (2nd ed.). New York: John Wiley & Sons. ISBN: 978-0471082010 |
| Alias≠ | MASE | sMAPE, SMAPE, symmetric MAPE |
| Apparentées | 4 | 4 |
| Résumé≠ | Mean Absolute Scaled Error is a scale-independent metric that measures prediction accuracy relative to a simple baseline (naive forecast). Introduced by Hyndman and Koehler (2006), MASE directly compares model performance to a reference method, overcoming limitations of MAPE and other percentage-based metrics. | Symmetric 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. |
| ScholarGateJeu de données ↗ |
|
|