Dear Matthieu, I don't know very well scikit. The Svm is implemented by Sequential Minimal Optimization (SMO). As for Terminated Ramps (TR) you can read this paper: /S. Merler and G. Jurman/* Terminated Ramp - Support Vector Machine: a nonparametric data dependent kernel* Neural Network, 19(10), 1597-1611, 2006.
/* da */ Matthieu Brucher ha scritto: > Hi, > > How does it compare to the elarn scikit, especially for the SVM part ? > How was it implemented ? > > Matthieu > > 2008/2/14, Davide Albanese <[EMAIL PROTECTED] <mailto:[EMAIL PROTECTED]>>: > > *Machine Learning Py* (MLPY) is a *Python/NumPy* based package for > machine learning. > The package now includes: > > * *Support Vector Machines* (linear, gaussian, polinomial, > terminated ramps) for 2-class problems > * *Fisher Discriminant Analysis* for 2-class problems > * *Iterative Relief* for feature weighting for 2-class problems > * *Feature Ranking* methods based on Recursive Feature Elimination > (rfe, onerfe, erfe, bisrfe, sqrtrfe) and Recursive Forward > Selection (rfs) > * *Input Data* functions > * *Confidence Interval* functions > > Requires Python <http://www.python.org/> >= 2.4 and NumPy > <http://www.scipy.org/> >= 1.0.3.* > MLPY* is a project of MPBA Group <http://mpa.fbk.eu/> (mpa.fbk.eu) at > Fondazione Bruno Kessler (www.fbk.eu). <http://www.fbk.eu/>* > MLPY* is free software. It is licensed under the GNU General Public > License (GPL) version 3 <http://www.gnu.org/licenses/gpl-3.0.html>. > > HomePage: mlpy.fbk.eu > _______________________________________________ > Numpy-discussion mailing list > [email protected] <mailto:[email protected]> > http://projects.scipy.org/mailman/listinfo/numpy-discussion > > > > > -- > French PhD student > Website : http://matthieu-brucher.developpez.com/ > Blogs : http://matt.eifelle.com and http://blog.developpez.com/?blog=92 > LinkedIn : http://www.linkedin.com/in/matthieubrucher _______________________________________________ Numpy-discussion mailing list [email protected] http://projects.scipy.org/mailman/listinfo/numpy-discussion
