DocumentCode
3600815
Title
Bayesian Fuzzy Clustering
Author
Glenn, Taylor C. ; Zare, Alina ; Gader, Paul D.
Author_Institution
Dept. of Comput. & Inf. Sci. & Eng., Univ. of Florida, Gainesville, FL, USA
Volume
23
Issue
5
fYear
2015
Firstpage
1545
Lastpage
1561
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.
Keywords
fuzzy set theory; inference mechanisms; parameter estimation; pattern clustering; probability; Bayesian fuzzy clustering model; Bayesian probabilistic model; fuzzy c-means approach; inference algorithm; model parameter estimation; particle filter inference technique; Bayes methods; Clustering algorithms; Data models; Mathematical model; Probabilistic logic; Proposals; Prototypes; Bayes methods; clustering algorithms; clustering methods; fuzzy sets; fuzzy systems; monte carlo methods; particle filters;
fLanguage
English
Journal_Title
Fuzzy Systems, IEEE Transactions on
Publisher
ieee
ISSN
1063-6706
Type
jour
DOI
10.1109/TFUZZ.2014.2370676
Filename
6955803
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