Controlling the False Discovery Rate for Feature Selection in High-resolution NMR Spectra

Successful implementation of feature selection in nuclear magnetic resonance (NMR) spectra not only improves classification ability, but also simplifies the entire modeling process and, thus, reduces computational and analytical efforts. Principal component analysis (PCA) and partial least squares (...

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Bibliographic Details
Main Authors: Kim, Seoung Bum, Chen, Victoria C. P., Park, Youngja, Ziegler, Thomas R., Jones, Dean P.
Format: Artigo
Language:Inglês
Published: 2008
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Article
Online Access:https://ncbi.nlm.nih.gov/pmc/articles/PMC3066443/
https://ncbi.nlm.nih.gov/pubmed/21461122
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/sam.10005
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