Bayesian nonparametric clustering based on Dirichlet processes
Following a review of some traditional methods of clustering, we review the Bayesian nonparametric framework for modelling object attribute differences. We focus on Dirichlet Process (DP) mixture models, in which the observed clusters in any particular data set are not viewed as belonging to a fixed...
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University College London (University of London)
2010
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| Online Access: | http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.565025 |