Binary grasshopper optimisation algorithm approaches for feature selection problems
作者：
Highlights：
• Three binary versions of Grasshopper Optimization Algorithm (BGOA) are proposed.
• Wrapper-based feature selection techniques are proposed using the BGOA algorithms.
• The proposed algorithms are benchmarked on 18 standard UCI datasets.
• The results are compared with 10 algorithms.
• The results show the merits of the proposed algorithms and feature selection methods.
摘要
•Three binary versions of Grasshopper Optimization Algorithm (BGOA) are proposed.•Wrapper-based feature selection techniques are proposed using the BGOA algorithms.•The proposed algorithms are benchmarked on 18 standard UCI datasets.•The results are compared with 10 algorithms.•The results show the merits of the proposed algorithms and feature selection methods.
论文关键词：Binary grasshopper optimisation algorithm,GOA,Optimisation,Feature selection,Classification
论文评审过程：Received 15 September 2017, Revised 2 September 2018, Accepted 7 September 2018, Available online 18 September 2018, Version of Record 3 October 2018.
论文官网地址：https://doi.org/10.1016/j.eswa.2018.09.015
