Anti-Noise Nonparallel Support Vector Machine with Margin Distribution

被引：0
|
作者：
Liu L.-M. [1 ]
Li P. [1 ]
Chu M.-X. [1 ]
Cai H.-B. [1 ]
机构：
[1] School of Electronic and Information Engineering, University of Science and Technology Liaoning, Liaoning, Anshan
来源：
Tien Tzu Hsueh Pao/Acta Electronica Sinica | 2023年 / 51卷 / 07期
基金：
中国国家自然科学基金;
关键词：
margin distribution; noise insensitive; nonparallel support vector machine; pattern recognition; structural information;
D O I：
10.12263/DZXB.20220268
中图分类号：
学科分类号：
摘要：
Because nonparallel support vector machine (NPSVM) is sensitive to noise and ignores the distributing structure of data, an anti-noise NPSVM with margin distribution (MD-ANPSVM) model is proposed. In MD-ANPSVM, each optimization problem simultaneously minimizes the L1-norm loss and improved hinge loss, which can ensure the stability of the model and reduce the adverse impact of noise and outliers. In addition, in MD-ANPSVM, the margin distribution described by the first- and second-order statistics is introduced. Each optimization problem simultaneously maximizes the margin mean and minimizes the margin variance, which results in better generalization performance. The experimental results on the UCI datasets and steel surface defects dataset show that MD-ANPSVM can achieve better generalization ability and strong robustness. © 2023 Chinese Institute of Electronics. All rights reserved.
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页码：1889 / 1897
页数：8
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