A reduced universum twin support vector machine for class imbalance learning

作者：

Highlights：

• A universum based algorithm is proposed for class imbalance learning.

• Universum learning is used for the first time to solve class imbalance problem.

• Reduced kernel is incorporated for reducing storage and computation cost.

• Proposed approach is useful for large scale class imbalanced datasets.

摘要

•A universum based algorithm is proposed for class imbalance learning.•Universum learning is used for the first time to solve class imbalance problem.•Reduced kernel is incorporated for reducing storage and computation cost.•Proposed approach is useful for large scale class imbalanced datasets.

论文关键词：Universum,Rectangular kernel,Class imbalance,Imbalance ratio,Twin support vector machine

论文评审过程：Received 22 June 2019, Revised 9 October 2019, Accepted 4 December 2019, Available online 7 January 2020, Version of Record 7 February 2020.

论文官网地址：https://doi.org/10.1016/j.patcog.2019.107150