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Twin Bounded Large Margin Distribution Machine

  • Haitao Xu
  • Brendan McCane
  • Lech Szymanski
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11320)

Abstract

In order to speed up the learning time of large margin distribution machine (LDM) and improve the generalization performance of twin bounded support vector machine (TBSVM), a novel method named twin bounded large margin distribution machine (TBLDM) is proposed in this paper. The central idea of TBLDM is to seek a pair of nonparallel hyperplanes by optimizing the positive and negative margin distributions on the base of TBSVM. The experimental results indicate that the proposed TBLDM is a fast, effective and robust classifier.

Keywords

Large margin distribution machine Twin bounded support vector machine Margin distribution Margin mean Margin variance 

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Department of Computer ScienceUniversity of OtagoOtagoNew Zealand

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