# What are the benefits and disadvantages to Lasso, Ridge, Elastic Net, and Non Negative Garrotte Regularization techniques?

I am implementing these four regularization techniques for linear regression of stock data in MATLAB but i noticed elastic net is just the sum of Ridge and Lasso, and i dont full understand how exactly Non Negative Garrotte Works as a regularization technique.

How does Garrotte work and why wouldnt you just always use elastic net over lasso and ridge? (Aside from computation complexity)

• I think it's probably true that many would opt for elastic nets over LASSO in general circumstances, but this implicitly assumes that you're selecting the value of the "mixing" parameter $\alpha$ such that you really do have a mix of L1 and L2 penalites, and are not simply selecting the LASSO or Ridge "by accident." – Sycorax says Reinstate Monica Dec 7 '14 at 21:48