view doc/v2_planning/existing_python_ml_libraries.txt @ 1114:de153244c8e5

added example file for the formulas.
author Frederic Bastien <nouiz@nouiz.org>
date Tue, 14 Sep 2010 13:33:45 -0400
parents 4eaf576c3e9a
children 0e12ea6ba661
line wrap: on
line source

Committee members: GD, DWF, IG, DE

This committee will investigate the possibility of interfacing and/or
borrowing from other Python machine learning libraries that exist out there.
Some questions that we need to answer:

 * How much should we try to interface with other libraries? 
 * What parts can we and should we implement ourselves and what should we leave
 to the other libraries?

Preliminary list of libraries to look at:

 * Pybrain   Razvan
 * MDP       Ian
 * Orange (http://www.ailab.si/orange/) Ian (but could trade)
 * PyML (http://pyml.sourceforge.net/)
 * mlpy (https://mlpy.fbk.eu/) Dumitru
 * APGL (http://packages.python.org/apgl/) Dumitru
 * MontePython (http://montepython.sourceforge.net/)  Guillaume (but could trade)
 * Shogun python bindings
 * libsvm python bindings   Ian (but could trade)
 * scikits.learn Guillaume (but could trade)

Also check out http://scipy.org/Topical_Software#head-fc5493250d285f5c634e51be7ba0f80d5f4d6443
- scipy.org's ``topical software'' section on Artificial Intelligence and
  Machine Learning