I the case of LinearRegression independent models are being fit for each response. But this is not the case for every multi-response estimator. Afaik, the multi response regression forests in sklearn will consider the correlation between features. -- Flavio
On Fri, Sep 5, 2014 at 11:03 AM, Philipp Singer <[email protected]> wrote: > Hey! > > I am currently working with data having multiple outcome variables. So for > example, my outcome I want to predict can be of multiple dimension. One line > of the data could look like the following: > > y = [10, 15] x = [13, 735478, 0.555, …] > > So I want to predict all dimensions of the outcome. > > I have seen that some algorithms can predict such multiple targets. I have > tried it with LinearRegression and it seems to work fine. > > I have not found a clear description of how this works though. Does it fit > one Regression separately for each outcome variable? > > Best, > Philipp > ------------------------------------------------------------------------------ > Slashdot TV. > Video for Nerds. Stuff that matters. > http://tv.slashdot.org/ > _______________________________________________ > Scikit-learn-general mailing list > [email protected] > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general ------------------------------------------------------------------------------ Slashdot TV. Video for Nerds. Stuff that matters. http://tv.slashdot.org/ _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
