[Numpy-discussion] MLPY - Machine Learning Py - Python/NumPy based package for machine learning

[Davide Albanese]

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 <albanese@fbk.eu <mailto:albanese@fbk.eu>>:
>
>     *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
>     _______________________________________________
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>
>
>
>
> -- 
> 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