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K-means clustering

version (3.3 KB) by Reza Ahmadzadeh
Simple implementation of the K-means algorithm for educational purposes


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 (2020). K-means clustering (, MATLAB Central File Exchange. Retrieved .

Comments and Ratings (2)

Alexander Laut

'mvnrnd' requires Statistics and Machine Learning Toolbox.

Tarique Ahmad

MATLAB Release Compatibility
Created with R2016b
Compatible with any release
Platform Compatibility
Windows macOS Linux