A hierarchical infinite generalized dirichlet mixture model with feature selection

Abstract

We propose a nonparametric Bayesian approach, based on hierarchical Dirichlet processes and generalized Dirichlet distributions, for simultaneous clustering and feature selection. The resulting statistical model is learned within a variational framework that we have developed. The merits of the developed model are shown via extensive simulations and experiments when applied to the challenging problem of images categorization. © 2014 Springer International Publishing Switzerland.