Dendrogram of mixing measures: Learning latent hierarchy and model selection for finite mixture models

arXiv:2403.01684v1 Announce Type: cross
Abstract: We present a new way to summarize and select mixture models via the hierarchical clustering tree (dendrogram) of an overfitted latent mixing measure. Our proposed method bridges agglomerative hierarchical clustering and mixture modeling. The dendrogram's construction is derived from the theory of convergence of the mixing measures, and as a result, we can both consistently select the true number of mixing components and obtain the pointwise optimal convergence rate for parameter estimation from the tree, …

abstract arxiv clustering construction hierarchical modeling model selection stat.me stat.ml theory tree type via