Tight clustering for large datasets with an application to gene expression data

This article proposes a practical and scalable version of the tight clustering algorithm. The tight clustering algorithm provides tight and stable relevant clusters as output while leaving a set of points as noise or scattered points, that would not go into any cluster. However, the computational li...

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Detalles Bibliográficos
Autores principales: Karmakar, Bikram, Das, Sarmistha, Bhattacharya, Sohom, Sarkar, Rohan, Mukhopadhyay, Indranil
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6395712/
https://www.ncbi.nlm.nih.gov/pubmed/30816195
http://dx.doi.org/10.1038/s41598-019-39459-w

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6395712/
https://www.ncbi.nlm.nih.gov/pubmed/30816195
http://dx.doi.org/10.1038/s41598-019-39459-w

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