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Evaluation of variable selection methods for random forests and omics data sets
Machine learning methods and in particular random forests are promising approaches for prediction based on high dimensional omics data sets. They provide variable importance measures to rank predictors according to their predictive power. If building a prediction model is the main goal of a study, o...
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| Publicado no: | Brief Bioinform |
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| Main Authors: | , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Oxford University Press
2017
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6433899/ https://ncbi.nlm.nih.gov/pubmed/29045534 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/bib/bbx124 |
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