পদ্ধতির তুলনা করুন

	বেয়েশীয়ান OLS (বেয়েশীয়ান অর্ডিনারি লিস্ট স্কোয়ারস রিগ্রেশন)	রিজ রিগ্রেশন
ক্ষেত্র	অর্থমিতি	যন্ত্র শিখন
পরিবার	Regression model	Machine learning
উদ্ভবের বছর	1971	1970
প্রবর্তক	Arnold Zellner	Hoerl, A.E. & Kennard, R.W.
ধরন	Bayesian linear regression	L2-regularized linear regression
মৌলিক উৎস	Zellner, A. (1971). An Introduction to Bayesian Inference in Econometrics. Wiley. ISBN: 978-0471169376	Hoerl, A.E. & Kennard, R.W. (1970). Ridge Regression: Biased Estimation for Nonorthogonal Problems. Technometrics, 12(1), 55–67.
অপর নাম	Bayesian linear regression, Bayesian normal regression, BLR, Bayesian least squares	Ridge Regresyonu, ridge regresyonu, L2-regularized regression, Tikhonov regularization
সম্পর্কিত	5	4
সারসংক্ষেপ	Bayesian OLS combines the classical linear regression likelihood with prior distributions over the coefficients and error variance. Rather than reporting point estimates, it produces full posterior distributions that quantify both estimated effects and their uncertainty. The approach is especially valuable when prior knowledge is available or when samples are small.	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.