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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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| Main Authors: | , , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2008
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| Assuntos: | |
| Acesso em linha: | 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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