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An efficient implementation of the k-means++ algorithm for clustering multivariate data. It has been shown that this algorithm has an upper bound for the expected value of the total intra-cluster distance which is log(k) competitive. Additionally, k-means++ usually converges in far fewer than vanilla k-means.
Cite As
Laurent S (2026). k-means++ (https://ch.mathworks.com/matlabcentral/fileexchange/28804-k-means), MATLAB Central File Exchange. Retrieved .
General Information
- Version 1.7.0.0 (1.74 KB)
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
| Version | Published | Release Notes | Action |
|---|---|---|---|
| 1.7.0.0 | Fixed bug with 1D datasets (thanks Xiaobo Li). |
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| 1.6.0.0 | Improved handling of overclustering (thanks Sid S) and added a screenshot. |
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| 1.5.0.0 | Small bugfix. |
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| 1.4.0.0 | Removed dependency on randi for R2008a or lower (thanks Cassie). |
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| 1.3.0.0 | Even faster, even less code and also fixed a few small bugs. |
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| 1.0.0.0 |
