手法を比較

	平均二乗誤差（MSE）	決定係数 (R²)
分野	モデル評価	モデル評価
系統	MCDM	MCDM
提唱年	1809	1896
提唱者	Carl Friedrich Gauss	Karl Pearson
種類	Squared-error loss function	Goodness-of-fit metric
原典	Gauss, C. F. (1809). Theoria Motus Corporum Coelestium in Sectionibus Conicis Solem Ambientium. Hamburg: Perthes and Besser.	Pearson, K. (1896). Mathematical contributions to the theory of evolution. Philosophical Transactions of the Royal Society A, 187, 253-318.
別名	MSE, L2 error, quadratic error	R², coefficient of determination, r2 score
関連	4	5
概要	Mean Squared Error is the foundational loss function for regression models, measuring the average squared deviation between predictions and observations. Originating from Gauss and Legendre's method of least squares (1805-1809), MSE is the basis for ordinary least squares regression and remains central to modern machine learning optimization.	The coefficient of determination, denoted R², measures the proportion of variance in the dependent variable explained by the independent variables in a regression model. Introduced by Karl Pearson in the late 19th century, R² is one of the most widely used metrics for assessing how well a model fits observed data.