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Non-negative matrix factorization by maximizing correntropy for cancer clustering
BACKGROUND: Non-negative matrix factorization (NMF) has been shown to be a powerful tool for clustering gene expression data, which are widely used to classify cancers. NMF aims to find two non-negative matrices whose product closely approximates the original matrix. Traditional NMF methods minimize...
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| Autors principals: | , , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
BioMed Central
2013
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3659102/ https://ncbi.nlm.nih.gov/pubmed/23522344 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/1471-2105-14-107 |
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