Efficient K-Means Clustering using JIT

Versione 1.0.0.0 (2,02 KB) da Yi Cao
A simple but fast tool for K-means clustering
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Aggiornato 16 apr 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.

Cita come

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

Compatibilità della release di MATLAB
Creato con R2007b
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Versione Pubblicato Note della release
1.0.0.0

correct bugs in examples