Shrinkage Strategies attempt to reduce the variance of fitted models by regularising the estimator of the model parameters. Intuitively, regularisation works by constraining the model coefficients, such that the variability of the model coefficients is limited or discouraged. Please explain the similarity between Ridge and Lasso. And please illustrate which one of Ridge and Lasso can make the coefficient equal to 0. If ?'s value is too large, what kind of outcome will we have?

. Ridge Regression RSS + . The Lasso RSS + > IB