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ESANN
2004

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Robust Bayesian Mixture Modelling

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Robust Bayesian Mixture Modelling

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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

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

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