Cargando…
The utility of clusters and a Hungarian clustering algorithm
Implicit in the k–means algorithm is a way to assign a value, or utility, to a cluster of points. It works by taking the centroid of the points and the value of the cluster is the sum of distances from the centroid to each point in the cluster. The aim in this paper is to introduce an alternative wa...
Autores principales: | Kume, Alfred, Walker, Stephen G. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8336801/ https://www.ncbi.nlm.nih.gov/pubmed/34347837 http://dx.doi.org/10.1371/journal.pone.0255174 |
Ejemplares similares
-
Analysis of Network Clustering Algorithms and Cluster Quality Metrics at Scale
por: Emmons, Scott, et al.
Publicado: (2016) -
Cross-Clustering: A Partial Clustering Algorithm with Automatic Estimation of the Number of Clusters
por: Tellaroli, Paola, et al.
Publicado: (2016) -
Clustering algorithms
por: Hartigan, John A
Publicado: (1975) -
Partitional clustering algorithms
por: Celebi, M
Publicado: (2015) -
Multicanonical cluster algorithm
por: Rummukainen, K.
Publicado: (1993)