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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...
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 |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2009
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2795965/ https://www.ncbi.nlm.nih.gov/pubmed/20018058 |
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