kmeans_varpar(X,k)

Version 1.0.1.0 (2.92 KB) by Stefan Philippo Pszczolkowski Parraguez
Implementation of K-means with Variance Partitioning initialization
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Updated 9 Aug 2017

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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 (2024). kmeans_varpar(X,k) (https://www.mathworks.com/matlabcentral/fileexchange/57229-kmeans_varpar-x-k), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2012b
Compatible with any release
Platform Compatibility
Windows macOS Linux
Acknowledgements

Inspired by: k-means++

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Version Published Release Notes
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.
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.
1.0.0.0