Centroid-Based Clustering with αβ-Divergences

Centroid-based clustering is a widely used technique within unsupervised learning algorithms in many research fields. The success of any centroid-based clustering relies on the choice of the similarity measure under use. In recent years, most studies focused on including several divergence measures...

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Detalles Bibliográficos
Autores principales: Sarmiento, Auxiliadora, Fondón, Irene, Durán-Díaz, Iván, Cruces, Sergio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514678/
https://www.ncbi.nlm.nih.gov/pubmed/33266911
http://dx.doi.org/10.3390/e21020196

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514678/
https://www.ncbi.nlm.nih.gov/pubmed/33266911
http://dx.doi.org/10.3390/e21020196

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