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Recursive SVM feature selection and sample classification for mass-spectrometry and microarray data
BACKGROUND: Like microarray-based investigations, high-throughput proteomics techniques require machine learning algorithms to identify biomarkers that are informative for biological classification problems. Feature selection and classification algorithms need to be robust to noise and outliers in t...
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| Autores principales: | , , , , , , , , , |
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| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
BioMed Central
2006
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| Materias: | |
| Acceso en línea: | https://ncbi.nlm.nih.gov/pmc/articles/PMC1456993/ https://ncbi.nlm.nih.gov/pubmed/16606446 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/1471-2105-7-197 |
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