On May 5, 9:57 am, William Cauchois <[email protected]> wrote: > In my opinion SVM functionality could be a useful addition to Sage.
Me too. In my opinion the optional SPKG for your binding should only be the first step. The ideal situation for the future is a SVM class in the statistics section of sage, where you can pose an SVM problem in general and then select which backend to use. Notice, that there are already two emerging possibilities for SVMs in Sage: The first one via R (if you install the "e1071" R package) and the second one is part of scipy.learn: http://fseoane.net/blog/2010/plot-the-maximum-margin-hyperplane-with-scikitslearn/ In general the goal of sage is to combine such tools under a common umbrella, just like it is currently developed for (mixed integer) linear programming in optimization by introducing a common class to pose such problems and a solve method, where you select the solver engine. H -- To post to this group, send an email to [email protected] To unsubscribe from this group, send an email to [email protected] For more options, visit this group at http://groups.google.com/group/sage-devel URL: http://www.sagemath.org
