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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...

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Detalles Bibliográficos
Autores principales:	Statnikov, Alexander, Wang, Lily, Aliferis, Constantin F
Formato:	Texto
Lenguaje:	English
Publicado:	BioMed Central 2008
Materias:	Research Article
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

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