विधियों की तुलना करें

	माध्यिका निरपेक्ष विचलन (MAD) आकलन	रिज रिग्रेशन
क्षेत्र	सांख्यिकी	मशीन अधिगम
परिवार	Regression model	Machine learning
उद्भव वर्ष	1974	1970
प्रवर्तक	Hampel (influence-curve treatment); classical robust statistics	Hoerl, A.E. & Kennard, R.W.
प्रकार	Robust scale estimator	L2-regularized linear regression
मौलिक स्रोत	Hampel, F. R. (1974). The Influence Curve and Its Role in Robust Estimation. Journal of the American Statistical Association, 69(346), 383-393.	Hoerl, A.E. & Kennard, R.W. (1970). Ridge Regression: Biased Estimation for Nonorthogonal Problems. Technometrics, 12(1), 55–67.
उपनाम	median absolute deviation, MAD scale estimator, robust scale estimation, Medyan Mutlak Sapma (MAD) Tahmini	Ridge Regresyonu, ridge regresyonu, L2-regularized regression, Tikhonov regularization
संबंधित	5	4
सारांश	Median 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.