Ridge regression is the method of estimating the coefficients of multiple-regression models in scenarios where the independent variables are highly correlated. The method provides improved efficiency in parameters estimation problems in exchange for a tolerable amount of bias meanwhile Lasso (Least absolute shrinkage and selection operator) is a regression analysis method that performs both variable selection and regularization to enhance the prediction ...
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