An Axiomatic Definition of Hierarchical Clustering
Machine Learning
2024-07-08 v1 Machine Learning
Statistics Theory
Statistics Theory
Abstract
In this paper, we take an axiomatic approach to defining a population hierarchical clustering for piecewise constant densities, and in a similar manner to Lebesgue integration, extend this definition to more general densities. When the density satisfies some mild conditions, e.g., when it has connected support, is continuous, and vanishes only at infinity, or when the connected components of the density satisfy these conditions, our axiomatic definition results in Hartigan's definition of cluster tree.
Keywords
Cite
@article{arxiv.2407.03574,
title = {An Axiomatic Definition of Hierarchical Clustering},
author = {Ery Arias-Castro and Elizabeth Coda},
journal= {arXiv preprint arXiv:2407.03574},
year = {2024}
}