Thresher: determining the number of clusters while removing outliers

BACKGROUND: Cluster analysis is the most common unsupervised method for finding hidden groups in data. Clustering presents two main challenges: (1) finding the optimal number of clusters, and (2) removing “outliers” among the objects being clustered. Few clustering algorithms currently deal directly...

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Detalles Bibliográficos
Autores principales: Wang, Min, Abrams, Zachary B., Kornblau, Steven M., Coombes, Kevin R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Methodology Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5759208/
https://www.ncbi.nlm.nih.gov/pubmed/29310570
http://dx.doi.org/10.1186/s12859-017-1998-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5759208/
https://www.ncbi.nlm.nih.gov/pubmed/29310570
http://dx.doi.org/10.1186/s12859-017-1998-9

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