ffcmw: The Fastest Fuzzy C-Means in the West!

Versión 1.0.4.0 (3,96 KB) por Marco Cococcioni
A fast implementation of the well-known fuzzy c-means clustering algorithm
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Actualizado 3 jul 2019

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When you need to clusterize data, fuzzy c-means is an appealing candidate, being it more robust and stable than the k-means clustering algorithm. This implementation is faster than that found in the Fuzzy Logic Toolbox (fcm.m). In addition, you can run it without having to buy the FL Toolbox. With this entry I want to stimulate the involvment of other users, to further speedup it and with the ultimate goal to eventually find the TRUE fastest fcm in the West!!

Citar como

Marco Cococcioni (2024). ffcmw: The Fastest Fuzzy C-Means in the West! (https://www.mathworks.com/matlabcentral/fileexchange/53029-ffcmw-the-fastest-fuzzy-c-means-in-the-west), MATLAB Central File Exchange. Recuperado .

Compatibilidad con la versión de MATLAB
Se creó con R2019a
Compatible con cualquier versión desde R2011a
Compatibilidad con las plataformas
Windows macOS Linux
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Más información sobre Fuzzy Logic Toolbox en Help Center y MATLAB Answers.

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Versión Publicado Notas de la versión
1.0.4.0

Added two demos.
1.0.3.0

Little code polishing
1.0.2.0

A minor improvement in the description of the function.
1.0.1.0

Added more comments to the code
1.0.0.0

Uploaded the picture!