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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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Detaylı Bibliyografya
Asıl Yazarlar: Liang, Yong, Liu, Cheng, Luan, Xin-Ze, Leung, Kwong-Sak, Chan, Tak-Ming, Xu, Zong-Ben, Zhang, Hai
Materyal Türü: Artigo
Dil:Inglês
Baskı/Yayın Bilgisi: BioMed Central 2013
Konular:
Online Erişim: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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