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

Version 1.0.4.0 (3,96 ko) par Marco Cococcioni
A fast implementation of the well-known fuzzy c-means clustering algorithm
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Mise à jour 3 juil. 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!!

Citation pour cette source

Marco Cococcioni (2026). ffcmw: The Fastest Fuzzy C-Means in the West! (https://fr.mathworks.com/matlabcentral/fileexchange/53029-ffcmw-the-fastest-fuzzy-c-means-in-the-west), MATLAB Central File Exchange. Extrait(e) le .

Compatibilité avec les versions de MATLAB
Créé avec R2019a
Compatible avec les versions R2011a et ultérieures
Plateformes compatibles
Windows macOS Linux
Catégories
En savoir plus sur Fuzzy Logic Toolbox dans Help Center et MATLAB Answers
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Version Publié le Notes de version
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!