k-means clustering

Version 1.0.0 (1.82 KB) by Orlando Ramirez Barron
The following is an implementation of the k-means algorithm for educational purpose. This algorithm is widely known in the signal processing
5.0
(6)
1.3K Downloads
Updated 9 Jun 2019

View License

The aim of the algorithm is to cluster n points (samples or observations) into k groups in which each point belongs to the cluster with the nearest mean. This process continues until there is no change in the clusters or the algorithm has reached the limit of iteration.
The algorithm has 3 values of interest: the number of points, k (number of clusters) and the number of iterations.
The code was designed in a way you can watch the movement of the cluster at each iteration.
If you are facing any trouble you can contact me by email.
my email is: orramirezba@ittepic.edu.mx

Cite As

Orlando Ramirez Barron (2024). k-means clustering (https://www.mathworks.com/matlabcentral/fileexchange/71796-k-means-clustering), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2016a
Compatible with any release
Platform Compatibility
Windows macOS Linux
Categories
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
1.0.0