A wrapper based binary bat algorithm with greedy crossover for attribute selection

作者：

Highlights：

• Multi-objective binary bat algorithm with greedy crossover is proposed.

• Premature convergence of the optimization algorithm is overcome.

• Highly predictive attributes producing high classification accuracy is obtained.

• Solution for obtaining high classification with reduced attributes is achieved.

摘要

•Multi-objective binary bat algorithm with greedy crossover is proposed.•Premature convergence of the optimization algorithm is overcome.•Highly predictive attributes producing high classification accuracy is obtained.•Solution for obtaining high classification with reduced attributes is achieved.

论文关键词：Attribute selection,Classification,Nature-inspired algorithm,SVM,Binary bat algorithm,Wrapper based algorithms

论文评审过程：Received 24 March 2020, Revised 25 July 2021, Accepted 29 August 2021, Available online 3 September 2021, Version of Record 16 September 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.115828