Bayesian Clustering

An approach to cluster analysis that applies Bayesian inference, constructing posterior distributions over clustering structures from prior distributions and likelihoods to quantify uncertainty in cluster assignments. Representative methods include Dirichlet process mixture models, which allow the number of clusters to be inferred from data.