On 09.02.2015 16:23, Alexandre Gramfort wrote: > the way to go is to*not* use fit_intercept in lasso_path and do it outside. > > we're going to remove this option.
Alight, thanks. I'm surprised that Lasso() and LassoCV() also have a fit_intercept=True set by default, but they don't throw a warning as lasso_path() does. So basically, in my workflow I have to "demean" all my target variables before using sklearn and "remean" them afterwards when writing out the predictions? Thanks Fabien ------------------------------------------------------------------------------ Dive into the World of Parallel Programming. The Go Parallel Website, sponsored by Intel and developed in partnership with Slashdot Media, is your hub for all things parallel software development, from weekly thought leadership blogs to news, videos, case studies, tutorials and more. Take a look and join the conversation now. http://goparallel.sourceforge.net/ _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
