Fast K-means clustering

Fast mex K-means clustering algorithm with possibility of K-mean++ initialization.

Description

Fast mex K-means clustering algorithm with possibility of K-mean++ initialization
(mex-interface modified from the original yael package https://gforge.inria.fr/projects/yael)

- Accept single/double precision input
- Support of BLAS/OpenMP for multi-core computation

Please run mexme_yael_kmeans.m to compile mex-files (be sure that mex -setup have been done at least one)

Run demo "test_yael_kmeans.m"

• Required Products: MATLAB
• MATLAB release: MATLAB 7.9 (R2009b)
• Other requirements: For a full usage, a OpenMP C compiler compliant such MSCV/Intel compiler/GCC. Shoud work with LCC but without OpenMP support.

[Sebastien PARIS]

Sepehr,
Can you indicate what is your OS, CPU and compiler used ? Did you recompile mex-files also ?

[Sepehr Farhand]

Matlab crashes w/ segmentation fault. I guess you have a loose pointer somewhere. "Segmentation violation detected"

[Sebastien PARIS]

Leila ...

It supports of course 3d vectors or more ...

[leila]

Does the code support 3d data?

[Sebastien PARIS]

Thank you for reporting ...
The update with correction will be published soon.

[Bonolo]

on the mac, need to change lib= '-lmwblas'; to libblas= '-lmwblas';

otherwise compiles fine.

[Sebastien PARIS]

Vladimir,

Did you compile mex-files first ?

Please run mexme_yael_kmeans.m to compile mex-files (be sure that mex -setup have been done at least one)

[Vladimir]

Using MSVC++ 2010 compiler, sample_mvgm throws an error when called in test_yael_kmeans:
"mu must be (d x 1 x M x n1 x ... x nl)"
where
mu = cat(3 , [-2.5 ; -3] , [0 ; 0] ,[ 5 ; 5]); %(d x 1 x M)