From: bthirion <bertrand.thir...@inria.fr>
To: scikit-learn@python.org
Sent: Wednesday, May 2, 2018 12:07 PM
Subject: Re: [scikit-learn] How does multiple target Ridge Regression work in
scikit learn?
The alpha parameter is shared for all problems; If you wnat to use differnt
parameters, you probably want to perform seprate fits.
Best,
Bertrand
On 02/05/2018 13:08, Peer Nowack wrote:
Hi all, I am struggling to understand the following: Scikit-learn offers a
multiple output version for Ridge Regression, simply by handing over a 2D array
[n_samples, n_targets], but how is it implemented?
http://scikit-learn.org/stable/modules/generated/sklearn.linear_model.Ridge.html
Is it correct to assume that each regression for each target is independent?
Under these circumstances, how can I adapt this to use individual alpha
regularization parameters for each regression? If I use GridSeachCV, I would
have to hand over a matrix of possible regularization parameters, or how would
that work? Thanks in advance - I have been searching for hours but could not
find anything on this topic. Peter
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