Krahasoni metodat

	Regresioni linear robust	Regresioni Huber
Fusha	Mësimi i makinës	Statistikë
Familja	Machine learning	Regression model
Viti i origjinës	1964–1987	1964
Krijuesi	Huber, P. J.; Rousseeuw, P. J.	Peter J. Huber
Lloji	Outlier-resistant supervised regression	Robust linear regression (M-estimation)
Burimi themelues	Huber, P. J. (1964). Robust Estimation of a Location Parameter. Annals of Mathematical Statistics, 35(1), 73–101.	Huber, P. J. (1964). Robust Estimation of a Location Parameter. Annals of Mathematical Statistics, 35(1), 73-101.
Emërtime të tjera	robust regression, M-estimator regression, Huber regression, outlier-resistant regression	Huber M-estimator, Huber loss regression, robust regression, Huber Regresyonu
Të lidhura	5	5
Përmbledhja	Robust linear regression fits a linear model between predictors and a continuous outcome while down-weighting or discarding influential outliers, preventing the few anomalous observations that OLS is famously sensitive to from distorting the entire estimated line. Major variants include Huber regression, iteratively reweighted least squares (IRLS), RANSAC, and Theil-Sen estimation.	Huber regression is a robust linear regression method, introduced by Peter J. Huber in 1964, that resists the influence of outliers by treating small and large residuals differently. It applies a squared (OLS-like) loss to small residuals and a milder absolute-value loss to large ones, so extreme observations cannot dominate the fit.