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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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Bibliografiske detaljer
Udgivet i:Brief Bioinform
Main Authors: Degenhardt, Frauke, Seifert, Stephan, Szymczak, Silke
Format: Artigo
Sprog:Inglês
Udgivet: Oxford University Press 2017
Fag:
Online adgang: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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