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Determinationskoefficienten (R²)×Root Mean Squared Error (RMSE)×
FagområdeModelevalueringModelevaluering
FamilieMCDMMCDM
Oprindelsesår18961809
OphavspersonKarl PearsonCarl Friedrich Gauss
TypeGoodness-of-fit metricDistance-based evaluation metric
Oprindelig kildePearson, K. (1896). Mathematical contributions to the theory of evolution. Philosophical Transactions of the Royal Society A, 187, 253-318. link ↗Gauss, C. F. (1809). Theoria Motus Corporum Coelestium in Sectionibus Conicis Solem Ambientium. Hamburg: Perthes and Besser. link ↗
AliasserR², coefficient of determination, r2 scoreRMSE, RMS error, quadratic mean error
Relaterede54
ResuméThe 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.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.
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ScholarGateSammenlign metoder: R-squared · Root Mean Squared Error. Hentet 2026-06-15 fra https://scholargate.app/da/compare