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A comprehensive comparison of random forests and support vector machines for microarray-based cancer classification
BACKGROUND: Cancer diagnosis and clinical outcome prediction are among the most important emerging applications of gene expression microarray technology with several molecular signatures on their way toward clinical deployment. Use of the most accurate classification algorithms available for microar...
| Autores principales: | , , |
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| Formato: | Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2008
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2492881/ https://www.ncbi.nlm.nih.gov/pubmed/18647401 http://dx.doi.org/10.1186/1471-2105-9-319 |