2013/2/5 Lars Buitinck <l.j.buiti...@uva.nl>: > 2013/2/5 Gael Varoquaux <gael.varoqu...@normalesup.org>: >> Do we need such genericity? Are there real practical gains to such >> modularity? My gut feeling would be to move forward with something >> simple, and make it performant statistical and computationaly for the >> common cases. > > Perhaps not, but would it hurt to have both? > > 2013/2/5 Olivier Grisel <olivier.gri...@ensta.org>: >> Argl. This does not feel like linear model model at all. I would >> rather put the transformer in sklearn.kernel_approximation . > > Indeed it doesn't :) +1 for kernel_approximations. > > However, if we do consider this a GLM, then that would warrant a > coef_/intercept_ API on the transformer.
To me it feels more like `components_` API (along with an additional `intercept_` or `thresholds_`). -- Olivier http://twitter.com/ogrisel - http://github.com/ogrisel ------------------------------------------------------------------------------ Free Next-Gen Firewall Hardware Offer Buy your Sophos next-gen firewall before the end March 2013 and get the hardware for free! Learn more. http://p.sf.net/sfu/sophos-d2d-feb _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
