I am doing regularization on linear regression and am observing something arguable: By increasing the $\lambda$ (shrinkage value), I observe that there is a point in which the training and testing error are the same. I just wonder if there is any justification behind this.


Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Browse other questions tagged or ask your own question.