A New Soft Computing Method for K-Harmonic Means Clustering

The K-harmonic means clustering algorithm (KHM) is a new clustering method used to group data such that the sum of the harmonic averages of the distances between each entity and all cluster centroids is minimized. Because it is less sensitive to initialization than K-means (KM), many researchers hav...

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Detalles Bibliográficos
Autores principales: Yeh, Wei-Chang, Jiang, Yunzhi, Chen, Yee-Fen, Chen, Zhe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5112810/
https://www.ncbi.nlm.nih.gov/pubmed/27846228
http://dx.doi.org/10.1371/journal.pone.0164754

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5112810/
https://www.ncbi.nlm.nih.gov/pubmed/27846228
http://dx.doi.org/10.1371/journal.pone.0164754

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