Evaluation of random forests performance for genome-wide association studies in the presence of interaction effects

Random forests (RF) is one of a broad class of machine learning methods that are able to deal with large-scale data without model specification, which makes it an attractive method for genome-wide association studies (GWAS). The performance of RF and other association methods in the presence of inte...

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Detalles Bibliográficos
Autores principales: Kim, Yoonhee, Wojciechowski, Robert, Sung, Heejong, Mathias, Rasika A, Wang, Li, Klein, Alison P, Lenroot, Rhoshel K, Malley, James, Bailey-Wilson, Joan E
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Proceedings
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2795965/
https://www.ncbi.nlm.nih.gov/pubmed/20018058

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2795965/
https://www.ncbi.nlm.nih.gov/pubmed/20018058

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