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

version (3.96 KB) by Marco Cococcioni
A fast implementation of the well-known fuzzy c-means clustering algorithm


Updated 03 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!!

Cite As

Marco Cococcioni (2021). ffcmw: The Fastest Fuzzy C-Means in the West! (, MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2019a
Compatible with R2011a and later releases
Platform Compatibility
Windows macOS Linux

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