吉林大学学报(工学版) ›› 2014, Vol. 44 ›› Issue (01): 137-141.doi: 10.13229/j.cnki.jdxbgxb201401024

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Feature selection algorithm based on random forest

YAO Deng-ju1,2, YANG Jing1, ZHAN Xiao-juan3   

  1. 1. College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China;
    2. School of Software, Harbin University of Science and Technology, Harbin 150040, China;
    3. College of Computer Science and Technology, Heilongjiang Institute of Technology, Harbin 150050, China
  • Received:2012-08-21 Online:2014-01-01 Published:2014-01-01

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Abstract:

A feature selection algorithm based on random forest (RFFS) is proposed. This algorithm adopts random forest algorithm as the basic tool, the classification accuracy as the criterion function. The sequential backward selection and generalized sequential backward selection methods are employed for feature selection. The experimental results on UCI datasets show that the RFFS algorithm has better performance in classification accuracy and feature selection subset than the other methods in literatures.

Key words: artificial intelligence, random forest, feature selection, wrapper

CLC Number: 

  • TP18

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