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Sparse logistic regression with a L(1/2) penalty for gene selection in cancer classification
BACKGROUND: Microarray technology is widely used in cancer diagnosis. Successfully identifying gene biomarkers will significantly help to classify different cancer types and improve the prediction accuracy. The regularization approach is one of the effective methods for gene selection in microarray...
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| Main Authors: | , , , , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
BioMed Central
2013
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3718705/ https://ncbi.nlm.nih.gov/pubmed/23777239 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/1471-2105-14-198 |
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