Bayesian Fuzzy Clustering
Taylor C. Glenn, Alina Zare, Paul Gader · IEEE Transactions on Fuzzy Systems · 2014
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.