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This question already has an answer here:

Can I implement ridge regression in terms of OLS regression? Is it even possible?

I am interested because scikit-learn supports non-negative least squares (NNLS), but not non-negative ridge regression. So, I'd like to transform my data as to be able to call the underlying NNLS function, but achieve ridge regression functionality.

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marked as duplicate by kjetil b halvorsen, Michael Chernick, Carl, mdewey, Peter Flom regression Sep 9 '17 at 11:44

This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.

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    $\begingroup$ Yes. See e.g. whuber's answer in stats.stackexchange.com/questions/69205. $\endgroup$ – amoeba Mar 25 '16 at 16:12
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    $\begingroup$ Also see here $\endgroup$ – Glen_b Mar 25 '16 at 16:29
  • $\begingroup$ How about a cross-validated form of ridge, calculating the best lambda? (penalty coefficient) $\endgroup$ – The Baron Mar 25 '16 at 16:30
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    $\begingroup$ Please see the answer in this thread, I think it addresses all your questions. $\endgroup$ – usεr11852 Mar 26 '16 at 3:55