kmeans_varpar(X,k)
Implementation of K-means with Variance Partitioning initialization
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Implementation of K-means with Variance Partitioning initialization. Variance Partitioning initialization is a deterministic way of initializing the data centroids, thus producing results that are repeatable and reproducible, without having to resort to tricks like seeding the pseudorandom number generator.
Cite As
Stefan Philippo Pszczolkowski Parraguez (2026). kmeans_varpar(X,k) (https://www.mathworks.com/matlabcentral/fileexchange/57229-kmeans_varpar-x-k), MATLAB Central File Exchange. Retrieved .
Acknowledgements
Inspired by: k-means++
General Information
- Version 1.0.1.0 (2.92 KB)
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
| Version | Published | Release Notes | Action |
|---|---|---|---|
| 1.0.1.0 | Removed loop that made sure that the number of returned centrers is equal to the specified k. This is arguably not necessary and since variance partitioning provides a deterministic result, there is potential for getting trapped in an infinite loop.
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| 1.0.0.0 |
