Bayesian Fuzzy Clustering

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Taylor C. Glenn, Alina Zare, Paul D. Gader

Published: 2015, Last Modified: 09 Nov 2025IEEE Trans. Fuzzy Syst. 2015EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: We present a Bayesian probabilistic model and inference algorithm for fuzzy clustering that provides expanded capabilities over the traditional Fuzzy C-Means approach. Additionally, we extend the Bayesian Fuzzy Clustering model to handle a variable number of clusters and present a particle filter inference technique to estimate the model parameters including the number of clusters. We show results on synthetic and real data and compare with other approaches.