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Procjena medijanske apsolutne devijacije (MAD)×Ridge Regression×
PodručjeStatistikaStrojno učenje
ObiteljRegression modelMachine learning
Godina nastanka19741970
TvoracHampel (influence-curve treatment); classical robust statisticsHoerl, A.E. & Kennard, R.W.
VrstaRobust scale estimatorL2-regularized linear regression
Temeljni izvorHampel, F. R. (1974). The Influence Curve and Its Role in Robust Estimation. Journal of the American Statistical Association, 69(346), 383-393. DOI ↗Hoerl, A.E. & Kennard, R.W. (1970). Ridge Regression: Biased Estimation for Nonorthogonal Problems. Technometrics, 12(1), 55–67. DOI ↗
Drugi nazivimedian absolute deviation, MAD scale estimator, robust scale estimation, Medyan Mutlak Sapma (MAD) TahminiRidge Regresyonu, ridge regresyonu, L2-regularized regression, Tikhonov regularization
Srodne54
SažetakMedian Absolute Deviation estimation is a robust measure of statistical dispersion that replaces the standard deviation when outliers are present. Rooted in the influence-curve framework formalised by Hampel (1974), it summarises the spread of a continuous variable using medians instead of means, so a single extreme value cannot distort the result.Ridge Regression is an L2-regularized linear regression method, introduced by Arthur Hoerl and Robert Kennard in 1970, that reduces multicollinearity by adding a penalty on the size of the coefficients. It shrinks coefficients toward zero without setting any of them exactly to zero, producing more stable estimates when predictors are highly correlated.
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ScholarGateUsporedite metode: MAD Estimation · Ridge Regression. Preuzeto 2026-06-18 s https://scholargate.app/hr/compare