Heterogeneous ensemble feature selection for network intrusion detection system

HIGHLIGHTS

• who: Yeshalem Gezahegn Damtew from the School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu, China have published the Article: Heterogeneous Ensemble Feature Selection for Network Intrusion Detection System, in the Journal: (JOURNAL)
• what: The authors evaluate the HEFS method with random forest J48 random and REP The main reason behind these problems may be a large number of features. The authors propose a Heterogeneous Ensemble Feature Selection (HEFS) method. The study proposes a heterogeneous ensemble feature selection method rather than an ensemble classifier to retain useful candidate features.
• how: This paper . . .
  

   

  

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