An association-based evolutionary ensemble method of variable selection
作者：
Highlights：
• A new ensemble method for variable selection is presented.
• A series of association rules is defined to discovery the combination variables.
• Performance of the proposed model is evaluated on several real-world datasets.
• Parameters impacting on the veracity and stability of the approach are evaluated.
• The approach is suit to deal with large-scale data and in parallelization.
摘要
•A new ensemble method for variable selection is presented.•A series of association rules is defined to discovery the combination variables.•Performance of the proposed model is evaluated on several real-world datasets.•Parameters impacting on the veracity and stability of the approach are evaluated.•The approach is suit to deal with large-scale data and in parallelization.
论文关键词：Knowledge discovery,Variable selection,Association-based ensemble,Evolutionary algorithm,Multiple linear regression
论文评审过程：Received 20 March 2018, Revised 24 December 2018, Accepted 14 January 2019, Available online 19 January 2019, Version of Record 26 January 2019.
论文官网地址：https://doi.org/10.1016/j.eswa.2019.01.039
