CLC number: TN911.7
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2008-12-26
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Liang TANG, Qi XUAN, Rong XIONG, Tie-jun WU, Jian CHU. A multi-class large margin classifier[J]. Journal of Zhejiang University Science A, 2009, 10(2): 253-262.
@article{title="A multi-class large margin classifier",
author="Liang TANG, Qi XUAN, Rong XIONG, Tie-jun WU, Jian CHU",
journal="Journal of Zhejiang University Science A",
volume="10",
number="2",
pages="253-262",
year="2009",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.A0820122"
}
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T1 - A multi-class large margin classifier
A1 - Liang TANG
A1 - Qi XUAN
A1 - Rong XIONG
A1 - Tie-jun WU
A1 - Jian CHU
J0 - Journal of Zhejiang University Science A
VL - 10
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SP - 253
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%@ 1673-565X
Y1 - 2009
PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.A0820122
Abstract: Currently there are two approaches for a multi-class support vector classifier (SVC). One is to construct and combine several binary classifiers while the other is to directly consider all classes of data in one optimization formulation. For a K-class problem (K>2), the first approach has to construct at least K classifiers, and the second approach has to solve a much larger optimization problem proportional to K by the algorithms developed so far. In this paper, following the second approach, we present a novel multi-class large margin classifier (MLMC). This new machine can solve K-class problems in one optimization formulation without increasing the size of the quadratic programming (QP) problem proportional to K. This property allows us to construct just one classifier with as few variables in the QP problem as possible to classify multi-class data, and we can gain the advantage of speed from it especially when K is large. Our experiments indicate that MLMC almost works as well as (sometimes better than) many other multi-class SVCs for some benchmark data classification problems, and obtains a reasonable performance in face recognition application on the AR face database.
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