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.
The work of REF , Bayesian Agglomerative Clustering with Coalescents, is a fully Bayesian approach for hierarchical clustering based on a prior over trees called Kingman's coalescent.
Bayesian Agglomerative Clustering with Coalescents
arXiv: Machine Learning
Mathematics Computer Science