Efficient K-Means Clustering using JIT

Version 1.0.0.0 (2,02 ko) par Yi Cao
A simple but fast tool for K-means clustering
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Mise à jour 16 avr. 2008

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This is a tool for K-means clustering. After trying several different ways to program, I got the conclusion that using simple loops to perform distance calculation and comparison is most efficient and accurate because of the JIT acceleration in MATLAB.

The code is very simple and well documented, hence is suitable for beginners to learn k-means clustering algorithm.

Numerical comparisons show that this tool could be several times faster than kmeans in Statistics Toolbox.

Citation pour cette source

Yi Cao (2024). Efficient K-Means Clustering using JIT (https://www.mathworks.com/matlabcentral/fileexchange/19344-efficient-k-means-clustering-using-jit), MATLAB Central File Exchange. Récupéré le .

Compatibilité avec les versions de MATLAB
Créé avec R2007b
Compatible avec toutes les versions
Plateformes compatibles
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Version Publié le Notes de version
1.0.0.0

correct bugs in examples