Evidence approximation in linear regression: A method that produces “automatically regularized” solutions.

Summary In this post, I look at a Bayesian treatment of the linear regression problem. Making use of basis functions allows you to model non-linear patterns in data, however taking this route usually requires that you regularize your solution. To find the best regularization parameter often requires cross validation, but by looking at a framework […]