A New Criterion for Improving Convergence of Fuzzy C-Means Clustering

A New Criterion for Improving Convergence of Fuzzy C-Means Clustering

One of the most used algorithms to solve the fuzzy clustering problem is Fuzzy C-Means; however, one of its main limitations is its high computational complexity. It is known that the efficiency of an algorithm depends, among other factors, on the strategies for its initialization and convergence. I...

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Bibliographic Details
Main Authors: Joaquín Pérez-Ortega, Carlos Fernando Moreno-Calderón, Sandra Silvia Roblero-Aguilar, Nelva Nely Almanza-Ortega, Juan Frausto-Solís, Rodolfo Pazos-Rangel, José María Rodríguez-Lelis
Format: Article
Language:English
Published: MDPI AG 2024-01-01
Series:Axioms
Subjects:
big data
clustering algorithm
convergence
data science
Fuzzy C-Means
Online Access:https://www.mdpi.com/2075-1680/13/1/35

Internet

https://www.mdpi.com/2075-1680/13/1/35

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