Robust hypergraph regularized non-negative matrix factorization for sample clustering and feature selection in multi-view gene expression data

BACKGROUND: As one of the most popular data representation methods, non-negative matrix decomposition (NMF) has been widely concerned in the tasks of clustering and feature selection. However, most of the previously proposed NMF-based methods do not adequately explore the hidden geometrical structur...

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Detalles Bibliográficos
Autores principales: Yu, Na, Gao, Ying-Lian, Liu, Jin-Xing, Wang, Juan, Shang, Junliang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6805321/
https://www.ncbi.nlm.nih.gov/pubmed/31639067
http://dx.doi.org/10.1186/s40246-019-0222-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6805321/
https://www.ncbi.nlm.nih.gov/pubmed/31639067
http://dx.doi.org/10.1186/s40246-019-0222-6

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