Efficient K-Means Clustering using JIT

版本 1.0.0.0 (2.0 KB) 作者: Yi Cao
A simple but fast tool for K-means clustering
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更新时间 2008/4/16

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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.

引用格式

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. 检索来源 .

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版本 已发布 发行说明
1.0.0.0

correct bugs in examples