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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...
Autores principales: | 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 |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3287568/ https://www.ncbi.nlm.nih.gov/pubmed/22784619 http://dx.doi.org/10.1186/1752-0509-5-S3-S13 |
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