K-means clustering

Simple implementation of the K-means algorithm for educational purposes


Updated 20 Jan 2018

View License

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 (2023). 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
Platform Compatibility
Windows macOS Linux
Find more on Statistics and Machine Learning Toolbox in Help Center and MATLAB Answers

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!
Version Published Release Notes