Clustering by Hill-Climbing: Consistency Results

Autor:	Arias-Castro, Ery, Qiao, Wanli
Rok vydání:	2022
Předmět:	Mathematics - Statistics Theory Mathematics - Classical Analysis and ODEs Statistics - Machine Learning
Druh dokumentu:	Working Paper
Popis:	We consider several hill-climbing approaches to clustering as formulated by Fukunaga and Hostetler in the 1970's. We study both continuous-space and discrete-space (i.e., medoid) variants and establish their consistency.
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2202.09023 Zobrazit plný text záznamu View this record from Arxiv