Improving Extreme Learning Machine by Competitive Swarm Optimization and its application for medical diagnosis problems

作者：

Highlights：

• Improved Extreme Learning Machine by Competitive Swarm Optimization is proposed.

• The proposed model is applied for 15 medical classification problems.

• The model outperforms in terms of accuracy, stability, complexity and time.

• Benchmark results confirm effectiveness of proposed model.

摘要

•Improved Extreme Learning Machine by Competitive Swarm Optimization is proposed.•The proposed model is applied for 15 medical classification problems.•The model outperforms in terms of accuracy, stability, complexity and time.•Benchmark results confirm effectiveness of proposed model.

论文关键词：Extreme Learning Machine,Evolutionary Extreme Learning Machine,ELM,Metaheuristic,Medical classification,Competitive Swarm Optimizer,CSO

论文评审过程：Received 10 October 2017, Revised 25 December 2017, Accepted 13 March 2018, Available online 14 March 2018, Version of Record 26 March 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.03.024