Twin SVM with a reject option through ROC curve

Dongyun Lin, Lei Sun, Kar Ann Toh, Jing Bo Zhang, Zhiping Lin

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)


This paper proposes a new method which embeds a reject option in twin support vector machine (RO-TWSVM) through the Receiver Operating Characteristic (ROC) curve for binary classification. The proposed RO-TWSVM enhances the classification robustness through inclusion of an effective rejection rule for potentially misclassified samples. The method is formulated based on a cost-sensitive framework which follows the principle of minimization of the expected cost of classification. Extensive experiments are conducted on synthetic and real-world data sets to compare the proposed RO-TWSVM with the original TWSVM without a reject option (TWSVM-without-RO) and the existing SVM with a reject option (RO-SVM). The experimental results demonstrate that our RO-TWSVM significantly outperforms TWSVM-without-RO, and in general, performs better than RO-SVM.

Original languageEnglish
Pages (from-to)1710-1732
Number of pages23
JournalJournal of the Franklin Institute
Issue number4
Publication statusPublished - 2018 Mar

Bibliographical note

Publisher Copyright:
© 2017 The Franklin Institute

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Signal Processing
  • Computer Networks and Communications
  • Applied Mathematics


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