You can get one alpha per target in the Ridge estimator (without CV). Then you would have to code the cv loop yourself.
Depending on how many target you have this can be more efficient than looping over targets as Alex suggests. Either way there is some coding to do unfortunately. Michael On Tue, Aug 7, 2018 at 6:05 AM, Alexandre Gramfort < alexandre.gramf...@inria.fr> wrote: > you should call RidgeCV on all targets separately. > > HTH > Alex > > On Tue, Aug 7, 2018 at 12:46 PM Christophe Pallier > <christo...@pallier.org> wrote: > > > > Hello, > > > > I'd like to use RidgeCV to find the optimal alpha for each colunm > (ntargets) of the DV variable. > > > > It lloks like itthe fit() computes a single alpha. Is there a way to > compute one alpha per column? > > > > > > > > > > -- > > -- > > Christophe Pallier <christo...@pallier.org> > > INSERM-CEA Cognitive Neuroimaging Lab, Neurospin, bat 145, > > 91191 Gif-sur-Yvette Cedex, France > > Tel: 00 33 1 69 08 79 34 > > Personal web site: http://www.pallier.org > > Lab web site: http://www.unicog.org > > _______________________________________________ > > scikit-learn mailing list > > scikit-learn@python.org > > https://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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