Methoden vergelijken

	Root Mean Squared Error (RMSE)	Gemiddelde Absolute Fout (MAE)
Vakgebied	Modelevaluatie	Modelevaluatie
Familie	MCDM	MCDM
Jaar van ontstaan	1809	1799
Grondlegger	Carl Friedrich Gauss	Pierre-Simon Laplace
Type	Distance-based evaluation metric	Robust distance-based metric
Oorspronkelijke bron	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.
Aliassen	RMSE, RMS error, quadratic mean error	MAE, L1 error, mean absolute deviation
Verwant	4	3
Samenvatting	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.