Imbalanced data classification using second-order cone programming support vector machines

作者：

Highlights：

• Novel robust classification approach for imbalanced data classification.

• Extension of LP-SVM formulation using second-order cone programming.

• Best classification performance is achieved in experiments on benchmark datasets.

摘要

•Novel robust classification approach for imbalanced data classification.•Extension of LP-SVM formulation using second-order cone programming.•Best classification performance is achieved in experiments on benchmark datasets.

论文关键词：Class-imbalanced data,Support Vector Machines,LP-SVM,SOCP-SVM

论文评审过程：Received 7 June 2013, Revised 2 October 2013, Accepted 23 November 2013, Available online 3 December 2013.

论文官网地址：https://doi.org/10.1016/j.patcog.2013.11.021