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Maximal conditional chi-square importance in random forests
Motivation: High-dimensional data are frequently generated in genome-wide association studies (GWAS) and other studies. It is important to identify features such as single nucleotide polymorphisms (SNPs) in GWAS that are associated with a disease. Random forests represent a very useful approach for...
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| Main Authors: | , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Oxford University Press
2010
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC2832825/ https://ncbi.nlm.nih.gov/pubmed/20130032 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/bioinformatics/btq038 |
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