k-means++

Version 1.7.0.0 (1.74 KB) by Laurent S
Cluster multivariate data using the k-means++ algorithm.
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(22)
14.3K Downloads
Updated 11 Feb 2013

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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 .

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

Inspired by: Kmeans Clustering

Inspired: kmeans_varpar(X,k), Sparsified K-Means

Version Published Release Notes
1.7.0.0

Fixed bug with 1D datasets (thanks Xiaobo Li).
1.6.0.0

Improved handling of overclustering (thanks Sid S) and added a screenshot.
1.5.0.0

Small bugfix.
1.4.0.0

Removed dependency on randi for R2008a or lower (thanks Cassie).
1.3.0.0

Even faster, even less code and also fixed a few small bugs.
1.0.0.0