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Matrix Factorization Methods for Python (pymf)
==============================================

What is PyMF?
-------------

Python Matrix Factorization (PyMF) is a module for several constrained/unconstrained 
matrix factorization (and related) methods. The module is early alpha and not very well 
tested.

PyMF currently includes the following methods:

    * Non-negative matrix factorization (NMF)
    * Convex non-negative matrix factorization (CNMF)
    * Semi non-negative matrix factorization (SNMF)
    * Archetypal analysis (AA)
    * Simplex volume maximization (SiVM)
    * Convex-hull non-negative matrix factorization (CHNMF)
    * Heirachical Convex-hull non-negative matrix factorization (HCHNMF)
    * Binary matrix factorization (BNMF)
    * Singular value decomposition (SVD)
    * Principal component analysis (PCA)
    * K-means clustering (Kmeans)
    * CUR decomposition (CUR)
    * Compaxt matrix decomposition (CMD) 

Where to get it
---------------

* Main website, documentation:  http://pymf.googlecode.com
* Contact email: cthurau at googlemail.com
* Contact email: richardweiss at richardweiss.org


Requires
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* Linux, Mac OS-X or Windows
* Python 2.5 or 2.6
* NumPy, Cvxopt, Scipy

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My extensions to the pymf library

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