[scikit-learn] How does multiple target Ridge Regression work in scikit learn?

[Peer Nowack]

Thanks, Bertrand - very helpful. Needed to consolidate this.

Peter

On 2 May 2018 at 13:07, bthirion <bertrand.thirion at inria.fr> wrote:

> 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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