Locally Adaptive Hierarchical Cluster Termination With Application To Individual Tree Delineation

Autor:	Richardson, Ashlin, Leckie, Donald
Rok vydání:	2022
Předmět:	Statistics - Machine Learning Computer Science - Machine Learning 62H30 (Primary) I.5.3 I.5.4
Druh dokumentu:	Working Paper
Popis:	A clustering termination procedure which is locally adaptive (with respect to the hierarchical tree of sets representative of the agglomerative merging) is proposed, for agglomerative hierarchical clustering on a set equipped with a distance function. It represents a multi-scale alternative to conventional scale dependent threshold based termination criteria. Comment: 8 pages, 14 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2212.00288 Zobrazit plný text záznamu View this record from Arxiv