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>:
*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/
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