The regularization paths for the ROC-optimizing support vector machines

Dohyun Kim, Seung Jun Shin

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


Rakotomamonjy (RO-CAI, pp 71–80, 2009) proposed an ROC-SVM that optimizes the receiver operating characteristic curve (ROC) particularly useful for unbalanced classification. In this article, we establish the piecewise linearity of the ROC-SVM solutions as a function of regularization parameter, and develop an efficient algorithm for computing the entire regularization paths of the ROC-SVM. Finally we develop an R package, rocsvm.path, now available in CRAN.

Original languageEnglish
Pages (from-to)264-275
Number of pages12
JournalJournal of the Korean Statistical Society
Issue number1
Publication statusPublished - 2020 Mar 1


  • Piecewise linearity
  • Receiver operating characteristic curve
  • Support vector machine
  • Unbalanced classification

ASJC Scopus subject areas

  • Statistics and Probability


Dive into the research topics of 'The regularization paths for the ROC-optimizing support vector machines'. Together they form a unique fingerprint.

Cite this