Timeline for Issues with ridge regression
Current License: CC BY-SA 3.0
4 events
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| Sep 4, 2013 at 17:19 | comment | added | O_Devinyak | Zero mean and unit variance should be preferred. If this still has no effect, then something goes wrong. The covariates may be completely irrelevant, or your cross-validation code contain a bug, or something else. It would be useful to see your beta's, mean squared errors and cross-validation mean squared errors for non-standardized and standardized models. | |
| Sep 4, 2013 at 17:17 | comment | added | David Marx |
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).
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| Sep 4, 2013 at 17:04 | comment | added | user34790 | 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 $\lambda$ | |
| Sep 4, 2013 at 16:24 | history | answered | O_Devinyak | CC BY-SA 3.0 |