Centroid mutation-based Search and Rescue optimization algorithm for feature selection and classification

作者：

Highlights：

• An efficient FSAR algorithm is proposed based on Fuzzy logic mutation.

• CEC-C06 2019 test suite is utilized for verification of FSAR performance.

• FSAR is proposed for biomedical classification tasks.

• FSAR is analyzed using various analysis metrics.

• The performance of the FSAR is better than other competitor algorithms.

摘要

•An efficient FSAR algorithm is proposed based on Fuzzy logic mutation.•CEC-C06 2019 test suite is utilized for verification of FSAR performance.•FSAR is proposed for biomedical classification tasks.•FSAR is analyzed using various analysis metrics.•The performance of the FSAR is better than other competitor algorithms.

论文关键词：Fuzzy logic,Centroid mutation,Feature Selection (FS),k-Nearest Neighbor (kNN),Medical diagnostic,Search and Rescue optimization algorithm (SAR)

论文评审过程：Received 12 May 2021, Revised 13 November 2021, Accepted 13 November 2021, Available online 3 December 2021, Version of Record 8 December 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.116235