Fast K-means clustering

Version 1.7.0.0 (119 KB) by Sebastien PARIS
Fast mex K-means clustering algorithm with possibility of K-mean++ initialization.
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4.2K Downloads
Updated 17 May 2021

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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_kmeans.m to compile mex-files (be sure that mex -setup have been done at least one)
Run demo "test_yael_kmeans.m"

Cite As

Sebastien PARIS (2024). Fast K-means clustering (https://www.mathworks.com/matlabcentral/fileexchange/33541-fast-k-means-clustering), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2009b
Compatible with any release
Platform Compatibility
Windows macOS Linux
Categories
Find more on Statistics and Machine Learning Toolbox in Help Center and MATLAB Answers
Acknowledgements

Inspired: Sparsified K-Means, Ziheng_GMM.zip

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Version Published Release Notes
1.7.0.0

Fix mwIndex pointers for modern Matlab. Currently works flawless when compiled with Intel compiler and linked with MKL.
1.6.0.0

- Fix compilation issue in mexme_yael_kmeans
- Include both mexw32 & mexw64 files in two separate files (unzip them in local dir in case of problem)
1.5.0.0

- Fix a bug in ndellipse introduced in the last update
1.4.0.0

-Correct a bug in mexme_yael_kmeans.m for Linux/Mac Os
1.3.0.0

-Correct a bug in randperm
1.2.0.0

- Minor changes
- Add spiral clustering example in the test file
1.1.0.0

- Add online help, minor changes
1.0.0.0