How does one perform least squares regression with http://en.wikipedia.org/wiki/Tikhonov_regularization" [Broken] when using a solver that takes matrix input?(adsbygoogle = window.adsbygoogle || []).push({});

To do the regularization, you add (Gamma*x)^2 to the term that you are minimizing. But what if you are using a solver where you can't directly add this to the residual sum of squares? In my case LAPACK xgels routines.

How can one transform the matrix to incorporate the regularization term?

I read the wiki article, however I took linear algebra in college almost a decade ago and am very rusty, so I am not able to figure this out myself

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# Least squares Ridge Regression - how to do with solver that takes matrix input?

Can you offer guidance or do you also need help?

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