Feature selection based on FDA and F-score for multi-class classification

作者：

Highlights：

• The feature ranking method is discussed based on Fisher discriminate analysis (FDA) and F-score.

• The relative distribution of different classes is considered in the paper.

• The method removes all insignificant features at a time, so it can effectively reduce computational cost.

• The advantages of the proposed method are discussed.

摘要

•The feature ranking method is discussed based on Fisher discriminate analysis (FDA) and F-score.•The relative distribution of different classes is considered in the paper.•The method removes all insignificant features at a time, so it can effectively reduce computational cost.•The advantages of the proposed method are discussed.

论文关键词：Feature selection,Feature ranking,Fisher discriminate analysis (FDA),F-score,Multi class

论文评审过程：Received 15 December 2016, Revised 10 February 2017, Accepted 18 February 2017, Available online 21 March 2017, Version of Record 30 March 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2017.02.049