Locally Adaptive Hierarchical Cluster Termination With Application To Individual Tree Delineation

2022/12/01 by Ashlin Richardson, Richardson, Ashlin, Donald G. Leckie +1
Computer Science · #62H30 (Primary) #Advanced Clustering Algorithms Research #Data Management and Algorithms #FOS: Computer and information sciences #I.5.3 #I.5.4 #Machine Learning (cs.LG) #Machine Learning (stat.ML)

paper · pdf · doi:10.48550/arxiv.2212.00288

openalex publication_date 2022/12/01 · openalex created_date 2022/12/13 · openalex updated_date 2026/07/28

Abstract

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.

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