Feature selection considering two types of feature relevancy and feature interdependency
作者：
Highlights：
• A novel feature selection method is proposed based on information theory.
• Our method divides feature relevancy into two categories.
• We performed experiments over 12 public data sets.
• Our method outperforms five competing methods in terms of accuracy.
• Our method selects few number of features when it achieves the highest accuracy.
摘要
•A novel feature selection method is proposed based on information theory.•Our method divides feature relevancy into two categories.•We performed experiments over 12 public data sets.•Our method outperforms five competing methods in terms of accuracy.•Our method selects few number of features when it achieves the highest accuracy.
论文关键词：Feature selection,Information theory,Feature relevancy,Feature interdependency
论文评审过程：Received 8 May 2017, Revised 5 October 2017, Accepted 6 October 2017, Available online 18 October 2017, Version of Record 5 November 2017.
论文官网地址：https://doi.org/10.1016/j.eswa.2017.10.016
