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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...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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BioMed Central
2013
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3659102/ https://www.ncbi.nlm.nih.gov/pubmed/23522344 http://dx.doi.org/10.1186/1471-2105-14-107 |