Updated 20 Jan 2018
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.
Reza Ahmadzadeh (2023). K-means clustering (https://www.mathworks.com/matlabcentral/fileexchange/65780-k-means-clustering), MATLAB Central File Exchange. Retrieved .
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