手法を比較

	二乗平均平方根誤差 (RMSE)	平均絶対誤差 (MAE)
分野	モデル評価	モデル評価
系統	MCDM	MCDM
提唱年	1809	1799
提唱者	Carl Friedrich Gauss	Pierre-Simon Laplace
種類	Distance-based evaluation metric	Robust distance-based metric
原典	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.
別名	RMSE, RMS error, quadratic mean error	MAE, L1 error, mean absolute deviation
関連	4	3
概要	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.