k-means clustering

Versione 1.0.0 (1,82 KB) da 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
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Aggiornato 9 giu 2019

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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

Cita come

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

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Versione Pubblicato Note della release
1.0.0