Robust Bayesian Mixture Modelling

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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-
Christopher M. Bishop, Markus Svensén
Added 30 Oct 2010
Updated 30 Oct 2010
Type Conference
Year 2004
Authors Christopher M. Bishop, Markus Svensén
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