Non-Negative Matrix Factorization (NMF) Implementation in C/Python using CBLAS/ATLAS Library

Cost Function: Kullback-Leibler Divergence.

Requires:

• python-dev or python3-dev
• libatlas3-base

Building

$ make py2 

or

$ make py3

Example

$ python run.py
V = 
[[ 1.  1.  1.  1.  1.]
 [ 0.  1.  0.  1.  0.]
 [ 0.  1.  0.  1.  0.]]
W . H ~
[[ 1.  1.  1.  1.  1.]
 [ 0.  1.  0.  1.  0.]
 [ 0.  1.  0.  1.  0.]]
Part 1 =
[[ 0.     0.769  0.     0.769  0.   ]
 [ 0.     1.     0.     1.     0.   ]
 [ 0.     1.     0.     1.     0.   ]]
Part 2 =
[[ 1.     0.231  1.     0.231  1.   ]
 [ 0.     0.     0.     0.     0.   ]
 [ 0.     0.     0.     0.     0.   ]]