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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...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2016
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| Materias: | |
| 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 |