A novel reconstructed training-set SVM with roulette cooperative coevolution for financial time series classification

作者：

Highlights：

• A novel SVM is proposed for high noise and unbalanced distribution data.

• Feature selection is improved by a novel method using the hierarchical relations in feature sets.

• Roulette algorithm is introduced into cooperative coevolution.

摘要

•A novel SVM is proposed for high noise and unbalanced distribution data.•Feature selection is improved by a novel method using the hierarchical relations in feature sets.•Roulette algorithm is introduced into cooperative coevolution.

论文关键词：Reconstructed training-set SVM,Cooperative coevolution,Time series,Classification

论文评审过程：Received 15 August 2018, Revised 7 December 2018, Accepted 6 January 2019, Available online 15 January 2019, Version of Record 22 January 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.01.022