Hi Jeremias.
I haven't thought that trough but shouldn't it be possible
to achieve the same effect by doing a linear transformation of your data
an labels
and then shrinking to zero?
Cheers,
Andy
On 03/21/2012 03:12 PM, Jeremias Engelmann wrote:
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
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