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رگرسیون کوانتایل (انواع ناپارامتری)×رگرسیون ریج (Ridge Regression)×
حوزهآماریادگیری ماشین
خانوادهRegression modelMachine learning
سال پیدایش19781970
پدیدآورKoenker & BassettHoerl, A.E. & Kennard, R.W.
نوعQuantile regression (nonparametric variants)L2-regularized linear regression
منبع بنیادینKoenker, R. & Bassett, G. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗Hoerl, A.E. & Kennard, R.W. (1970). Ridge Regression: Biased Estimation for Nonorthogonal Problems. Technometrics, 12(1), 55–67. DOI ↗
نام‌های دیگرquantile regression, median regression, distribution-free quantile regression, Kantil Regresyon (Nonparametric Varyantlar)Ridge Regresyonu, ridge regresyonu, L2-regularized regression, Tikhonov regularization
مرتبط54
خلاصهQuantile regression, introduced by Koenker and Bassett in 1978, models a chosen conditional quantile (such as the median or the 25th and 75th percentiles) of a continuous outcome rather than its mean. Its nonparametric variants fit these quantile relationships without assuming a distribution for the errors, making them a robust complement to mean-based regression on skewed data.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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ScholarGateمقایسهٔ روش‌ها: Nonparametric Quantile Regression · Ridge Regression. بازیابی‌شده در 2026-06-17 از https://scholargate.app/fa/compare