Comparer des méthodes

	Score de Brier	Erreur Absolue Moyenne (EAM)
Domaine	Évaluation de modèles	Évaluation de modèles
Famille	MCDM	MCDM
Année d'origine	1950	1799
Auteur d'origine	Glenn W. Brier	Pierre-Simon Laplace
Type	Loss function	Robust distance-based metric
Source fondatrice	Brier, G. W. (1950). Verification of forecasts expressed in terms of probability. Monthly Weather Review, 78(1), 1-3.	Laplace, P. S. (1799). Traité de Mécanique Céleste. Paris: J.B.M. Duprat.
Alias	Mean Squared Probability Error	MAE, L1 error, mean absolute deviation
Apparentées	3	3
Résumé	The Brier score measures the mean squared difference between predicted probabilities and actual binary outcomes. It is a simple, interpretable metric for evaluating the accuracy of probabilistic predictions, particularly in weather forecasting and medical diagnosis.	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.