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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