An implementation of three different types of Bayesian clustering methods: mixture models, stochastic block models, and species archetype models. The number of clusters is automatically estimated from the data using a Bayesian nonparametric approach based on truncated Stick-Breaking priors.
|Author||Denis Valle <email@example.com>|
|Maintainer||Denis Valle <firstname.lastname@example.org>|
|Package repository||View on GitHub|
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