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r2VIM: A new variable selection method for random forests in genome-wide association studies.

Silke SzymczakEmily Rose HolzingerAbhijit DasguptaJames D. MalleyAnne M. MolloyJames L. MillsLawrence C. BrodyDwight StambolianJoan E. Bailey-Wilson
Published in: BioData Min. (2016)
Keyphrases
  • variable selection
  • cross validation
  • random forests
  • clustering method
  • logistic regression
  • machine learning methods
  • statistical methods
  • random forest
  • similarity measure
  • model selection