On Wed, Mar 21, 2012 at 08:09:26PM -0400, David Warde-Farley wrote: > I think it's less about disagreeing with libsvm than disagreeing with the > notation of every textbook presentation I know of. I agree that libsvm is no > golden calf.
But it is also the case for the lasso: the loss term is the sum of the sample-level losses, and not the mean of these, (I just just in Tibshirani's paper and the 'Elements of statistical learning') and no library implements the lasso with a non-scaled version of the penalty. I think that many textbooks are just using the simplest possible formulation and no worrying about details like this one. There are many important details that are never mentionned in textbooks. > > That said, I agree with James that the docs should be much more > > explicit about what is going on, and how what we have differs from > > libsvm. > I think that renaming sklearn's scaled version of "C" is probably a > start. Using the name "C" for something other than what everyone else > means by "C" violates the principle if least surprise quite severely. > If they saw "zeta" or "Francis" or "unicorn", most people will not > assume it is a moniker for C but refer to the documentation for an > explanation. That might be a valid solution, also I don't think that it is as important as you say due to my above point. Gael ------------------------------------------------------------------------------ This SF email is sponsosred by: Try Windows Azure free for 90 days Click Here http://p.sf.net/sfu/sfd2d-msazure _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
