Inference of genetic networks using random forests: performance improvement using a new variable importance measure

HIGHLIGHTS

• who: CBI from the Faculty of Engineering, Tottori University, Koyama-minami, Tottori, Japan have published the research work: Inference of genetic networks using random forests: Performance improvement using a new variable importance measure, in the Journal: (JOURNAL)
• what: Among the various methods so far proposed for genetic network inference this study focuses on the random-forest-based methods. The authors therefore propose an alternative measure what the authors call u2113u2113the random-input variable importance measure `` and design a new inference method that uses the proposed measure in place of the standard measure in the existing . . .
  

   

  

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