K-means clustering

Version 1.0.0.0 (3.3 KB) by Reza Ahmadzadeh
Simple implementation of the K-means algorithm for educational purposes
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Updated 20 Jan 2018

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This is a simple implementation of the K-means algorithm for educational purposes. k-means clustering is a method of vector quantization, originally from signal processing, that is popular for cluster analysis in data mining. k-means clustering aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean, serving as a prototype of the cluster. This results in a partitioning of the data space into Voronoi cells.

Cite As

Reza Ahmadzadeh (2024). K-means clustering (https://www.mathworks.com/matlabcentral/fileexchange/65780-k-means-clustering), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2016b
Compatible with any release
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Version Published Release Notes
1.0.0.0