Comparison of a genetic algorithm to grammatical evolution for automated design of genetic programming classification algorithms
作者：
Highlights：
• Automated design of Genetic Programming classification algorithms is presented.
• Automated design uses a genetic algorithm and grammatical evolution.
• The approach is trained and tested using real-world binary and multi-class data.
• Grammatical evolution designed classifiers perform better for binary classification.
• Genetic algorithm designed classifiers perform better for multi-classification.
摘要
•Automated design of Genetic Programming classification algorithms is presented.•Automated design uses a genetic algorithm and grammatical evolution.•The approach is trained and tested using real-world binary and multi-class data.•Grammatical evolution designed classifiers perform better for binary classification.•Genetic algorithm designed classifiers perform better for multi-classification.
论文关键词：Genetic programming,Genetic algorithm,Grammatical evolution,Automated design,Classification
论文评审过程：Received 29 October 2017, Revised 17 March 2018, Accepted 18 March 2018, Available online 19 March 2018, Version of Record 1 April 2018.
论文官网地址：https://doi.org/10.1016/j.eswa.2018.03.030
