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arXiv 0907.0781stat.ML

Bayesian Agglomerative Clustering with Coalescents

Yee Whye Teh, Hal Daumé, Daniel Roy

英文摘要:

We introduce a new Bayesian model for hierarchical clustering based on a prior over trees called Kingman's coalescent. We develop novel greedy and sequential Monte Carlo inferences which operate in a bottom-up agglomerative fashion. We show experimentally the superiority of our algorithms over others, and demonstrate our approach in document clustering and phylolinguistics.

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