Comparar métodos

	R-quadrado ajustado (R²_adj)	Erro Quadrático Médio da Raiz (RMSE)
Área	Avaliação de modelos	Avaliação de modelos
Família	MCDM	MCDM
Ano de origem	1961	1809
Autor original	Henri Theil	Carl Friedrich Gauss
Tipo	Penalized goodness-of-fit metric	Distance-based evaluation metric
Fonte seminal	Theil, H. (1961). Economic Forecasts and Policy. Amsterdam: North-Holland Publishing Company.	Gauss, C. F. (1809). Theoria Motus Corporum Coelestium in Sectionibus Conicis Solem Ambientium. Hamburg: Perthes and Besser.
Outros nomes	Adjusted R², R²_adj	RMSE, RMS error, quadratic mean error
Relacionados	5	4
Resumo	Adjusted R² is a corrected version of the coefficient of determination that accounts for the number of predictors in a regression model. Introduced by Henri Theil in 1961, it addresses the fundamental limitation of standard R²: the tendency to increase whenever any predictor is added, regardless of whether that predictor contributes meaningfully to explaining the target variable.	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.