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