A score function for Bayesian cluster analysis
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2019-05-27 v1
Abstract
We propose a score function for Bayesian clustering. The function is parameter free and captures the interplay between the within cluster variance and the between cluster entropy of a clustering. It can be used to choose the number of clusters in well-established clustering methods such as hierarchical clustering or -means algorithm.
Keywords
Cite
@article{arxiv.1905.10209,
title = {A score function for Bayesian cluster analysis},
author = {John Noble and Łukasz Rajkowski},
journal= {arXiv preprint arXiv:1905.10209},
year = {2019}
}
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12 pages