Robust Bayesian Mixture Modelling

Abstract. Bayesian approaches to density estimation and clustering using mixture distributions allow the automatic determination of the number of components in the mixture. Previous treatments have focussed on mixtures having Gaussian components, but these are well known to be sensitive to outliers. This can lead to excessive sensitivity to small numbers of data points and consequent overestimates of the number of components. In this paper we develop a Bayesian approach to mixture modelling based on Student-

• Type: Conference
• Year: 2004
• Where: ESANN
• Authors: Christopher M. Bishop, Markus Svensén
• Keywords: ESANN 2004, ESANN 2007, Gaussian Components, Mixture Distributions, Student-Ø Distribution