Hi
I'm using scikit learn's linear model's ridge regression to do ridge
regression with large sparse matrices.
I know that, by design, ridge regression penalizes parameters for moving
away from zero. What I actually want is to penalize parameters to move away
from a certain prior (each parameter has a different prior).
I was wondering if that sort of thing is coming in a newer version of
scikit learn or what type of changes I would have to make to the code for
this to work.
Thank you very much
Sincerely yours
------------------------------------------------------------------------------
This SF email is sponsosred by:
Try Windows Azure free for 90 days Click Here
http://p.sf.net/sfu/sfd2d-msazure
_______________________________________________
Scikit-learn-general mailing list
Scikit-learn-general@lists.sourceforge.net
https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
