Novel Artificial Immune Networks-based optimization of shallow machine learning (ML) classifiers

作者：

Highlights：

• Artificial immune network (AIN) for optimizing machine learning algorithms.

• Convergence analysis of the proposed optimization algorithm is presented.

• Successful experimentation on many benchmark machines learning datasets.

• Achieved classification performance boost of 2%–9%.

摘要

•Artificial immune network (AIN) for optimizing machine learning algorithms.•Convergence analysis of the proposed optimization algorithm is presented.•Successful experimentation on many benchmark machines learning datasets.•Achieved classification performance boost of 2%–9%.

论文关键词：Artificial Immune Network (AIN),Echo State Network (ESN),Extreme Learning Machine (ELM),Support Vector Machine (SVM),Hyper-Parameters Optimization

论文评审过程：Received 17 September 2019, Revised 20 June 2020, Accepted 31 July 2020, Available online 6 August 2020, Version of Record 7 September 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113834