Efficient K-Means Clustering using JIT

Versión 1.0.0.0 (2,02 KB) por Yi Cao
A simple but fast tool for K-means clustering
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Actualizado 16 abr 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.

Citar como

Yi Cao (2025). Efficient K-Means Clustering using JIT (https://la.mathworks.com/matlabcentral/fileexchange/19344-efficient-k-means-clustering-using-jit), MATLAB Central File Exchange. Recuperado .

Compatibilidad con la versión de MATLAB
Se creó con R2007b
Compatible con cualquier versión
Compatibilidad con las plataformas
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Más información sobre Statistics and Machine Learning Toolbox en Help Center y MATLAB Answers.
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Versión Publicado Notas de la versión
1.0.0.0

correct bugs in examples