Thanks, Bertrand - very helpful. Needed to consolidate this. Peter
On 2 May 2018 at 13:07, bthirion <bertrand.thir...@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 > > > _______________________________________________ > scikit-learn mailing > listscikit-learn@python.orghttps://mail.python.org/mailman/listinfo/scikit-learn > > > > _______________________________________________ > scikit-learn mailing list > scikit-learn@python.org > https://mail.python.org/mailman/listinfo/scikit-learn > >
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