# Issues with ridge regression

I am running ridge regression on some data using a series of regularization params from 0.0001 to 1000. I was amazed to see that high values of lambda param 500-1000 is giving better results with cross validation.

Is it possible to get better results on such high lambda values?

• So do I need to scale them within the range of [0 1] or zero mean unit variance is enough. I tried to standardize the inputs and outputs to have zero mean and unit variance but still it is not good enough. I still get very high value for $\lambda$ – user34790 Sep 4 '13 at 17:04
• centering your data and standardizing to unit variance is fine. This is actually how the penalize and glmnet packages in R standardize. Another option is to standardize to unit norm, which is often recommended for Lasso regression (which are similar to ridge regression). – David Marx Sep 4 '13 at 17:17