Machine-learned cluster identification in high-dimensional data

BACKGROUND: High-dimensional biomedical data are frequently clustered to identify subgroup structures pointing at distinct disease subtypes. It is crucial that the used cluster algorithm works correctly. However, by imposing a predefined shape on the clusters, classical algorithms occasionally sugge...

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Detalles Bibliográficos
Autores principales: Ultsch, Alfred, Lötsch, Jörn
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2017
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5313598/
https://www.ncbi.nlm.nih.gov/pubmed/28040499
http://dx.doi.org/10.1016/j.jbi.2016.12.011

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5313598/
https://www.ncbi.nlm.nih.gov/pubmed/28040499
http://dx.doi.org/10.1016/j.jbi.2016.12.011

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