Kmeans Clustering

Version 2.0.0.0 (3,31 ko) par Mo Chen
Super fast and terse kmeans clustering.
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Mise à jour 13 mars 2017

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This is a super duper fast implementation of the kmeans clustering algorithm. The code is fully vectorized and extremely succinct. It is much much faster than the Matlab builtin kmeans function. The kmeans++ seeding algorithm is also included (kseeds.m) for good initialization. Therefore, this package is not only for coolness, it is indeed practical.
Please try the demo script in the package.

Detail explanation of this algorithm can be found in following blog post:
http://statinfer.wordpress.com/2011/12/12/efficient-matlab-ii-kmeans-clustering-algorithm/

This function is now a part of the PRML toolbox (http://www.mathworks.com/matlabcentral/fileexchange/55826-pattern-recognition-and-machine-learning-toolbox).

Citation pour cette source

Mo Chen (2024). Kmeans Clustering (https://www.mathworks.com/matlabcentral/fileexchange/24616-kmeans-clustering), MATLAB Central File Exchange. Extrait(e) le .

Compatibilité avec les versions de MATLAB
Créé avec R2016b
Compatible avec toutes les versions
Plateformes compatibles
Windows macOS Linux

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kmeans/

Version Publié le Notes de version
2.0.0.0

tweak and require Matlab R2016b or later
finalize, I'm done with kmeans.
1.9.0.0

tuning
fix incompatibility issue with newer version of Matlab, due to the stupid API change of function unique()
update tags
1.7.0.0

Cleaning up
1.5.0.0

remove empty clusters according to suggestion
1.4.0.0

remove empty clusters according to suggestion
1.3.0.0

fix a bug for 1d data
1.2.0.0

update the files and description
1.0.0.0