Kernelized partial least squares for feature reduction and classification of gene microarray data

BACKGROUND: The primary objectives of this paper are: 1.) to apply Statistical Learning Theory (SLT), specifically Partial Least Squares (PLS) and Kernelized PLS (K-PLS), to the universal "feature-rich/case-poor" (also known as "large p small n", or "high-dimension, low-samp...

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Detalhes bibliográficos
Main Authors: Land, Walker H, Qiao, Xingye, Margolis, Daniel E, Ford, William S, Paquette, Christopher T, Perez-Rogers, Joseph F, Borgia, Jeffrey A, Yang, Jack Y, Deng, Youping
Formato: Artigo
Idioma:Inglês
Publicado em: BioMed Central 2011
Assuntos:
Research Article
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC3287568/
https://ncbi.nlm.nih.gov/pubmed/22784619
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/1752-0509-5-S3-S13
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