Comparer des méthodes

	Erreur quadratique moyenne (RMSE)	Erreur Absolue Moyenne (EAM)
Domaine	Évaluation de modèles	Évaluation de modèles
Famille	MCDM	MCDM
Année d'origine	1809	1799
Auteur d'origine	Carl Friedrich Gauss	Pierre-Simon Laplace
Type	Distance-based evaluation metric	Robust distance-based metric
Source fondatrice	Gauss, C. F. (1809). Theoria Motus Corporum Coelestium in Sectionibus Conicis Solem Ambientium. Hamburg: Perthes and Besser.	Laplace, P. S. (1799). Traité de Mécanique Céleste. Paris: J.B.M. Duprat.
Alias	RMSE, RMS error, quadratic mean error	MAE, L1 error, mean absolute deviation
Apparentées	4	3
Résumé	Root Mean Squared Error is a widely used metric that measures the average magnitude of prediction errors in regression models. Originating from Carl Friedrich Gauss's work on least-squares estimation (1809), RMSE quantifies how far predictions deviate from observed values by averaging the squared differences and taking the square root.	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.