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2018 | OriginalPaper | Chapter

Twin Bounded Large Margin Distribution Machine

Authors : Haitao Xu, Brendan McCane, Lech Szymanski

Published in: AI 2018: Advances in Artificial Intelligence

Publisher: Springer International Publishing

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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.

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Footnotes
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Metadata
Title
Twin Bounded Large Margin Distribution Machine
Authors
Haitao Xu
Brendan McCane
Lech Szymanski
Copyright Year
2018
Book
AI 2018: Advances in Artificial Intelligence

Print ISBN: 978-3-030-03990-5

Electronic ISBN: 978-3-030-03991-2

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-030-03991-2_64

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