Structural regularized twin support vector machine based on within-class scatter and between-class scatter

doi:10.19682/j.cnki.1005-8885.2021.2004

中国邮电高校学报(英文) ›› 2021, Vol. 28 ›› Issue (4): 39-52.doi: 10.19682/j.cnki.1005-8885.2021.2004

• Artificial Intelligence • 上一篇下一篇

Structural regularized twin support vector machine based on within-class scatter and between-class scatter

Wu Qing, Fu Yanlin, Fan Jiulun, Ma Tianlu

1. School of Automation, Xi'an University of Posts and Telecommunications, Xi'an 710121, China
2. School of Telecommunication and Information Engineering, Xi'an University of Posts and Telecommunications, Xi'an 710121, China

收稿日期:2020-12-08 修回日期:2021-06-06 接受日期:2021-07-29 出版日期:2021-08-31 发布日期:2021-10-11
通讯作者: Corresponding author: Wu Qing, E-mail: xiyouwuq@126.com E-mail:xiyouwuq@126.com
基金资助:
The authors thank the anonymous reviewers for their constructive comments and suggestions. This work was supported
in part by the National Natural Science Foundation of China (51875457), Natural Science Foundation of Shaanxi Province of
China (2021JQ-701) and Xi'an Science and Technology Plan Project (2020KJRC0109).

Structural regularized twin support vector machine based on within-class scatter and between-class scatter

Wu Qing, Fu Yanlin, Fan Jiulun, Ma Tianlu

1. School of Automation, Xi'an University of Posts and Telecommunications, Xi'an 710121, China
2. School of Telecommunication and Information Engineering, Xi'an University of Posts and Telecommunications, Xi'an 710121, China

Received:2020-12-08 Revised:2021-06-06 Accepted:2021-07-29 Online:2021-08-31 Published:2021-10-11
Contact: Corresponding author: Wu Qing, E-mail: xiyouwuq@126.com E-mail:xiyouwuq@126.com
Supported by:
The authors thank the anonymous reviewers for their constructive comments and suggestions. This work was supported
in part by the National Natural Science Foundation of China (51875457), Natural Science Foundation of Shaanxi Province of
China (2021JQ-701) and Xi'an Science and Technology Plan Project (2020KJRC0109).

摘要/Abstract

摘要： Robust minimum class variance twin support vector machine (RMCV-TWSVM) presented previously gets better classification performance than the classical TWSVM. The RMCV-TWSVM introduces the class variance matrix of positive and negative samples into the construction of two hyperplanes. However, it does not consider the total structure information of all the samples, which can substantially reduce its classification accuracy. In this paper, a new algorithm named structural regularized TWSVM based on within-class scatter and between-class scatter (WSBS-STWSVM) is put forward. The WSBS-STWSVM can make full use of the total within-class distribution information and between-class structure information of all the samples. The experimental results illustrate high classification accuracy and strong generalization ability of the proposed algorithm.

关键词: generalization ability, twin support vector machine, within-class scatter, between-class scatter

Abstract: Robust minimum class variance twin support vector machine (RMCV-TWSVM) presented previously gets better classification performance than the classical TWSVM. The RMCV-TWSVM introduces the class variance matrix of positive and negative samples into the construction of two hyperplanes. However, it does not consider the total structure information of all the samples, which can substantially reduce its classification accuracy. In this paper, a new algorithm named structural regularized TWSVM based on within-class scatter and between-class scatter (WSBS-STWSVM) is put forward. The WSBS-STWSVM can make full use of the total within-class distribution information and between-class structure information of all the samples. The experimental results illustrate high classification accuracy and strong generalization ability of the proposed algorithm.

Key words: generalization ability, twin support vector machine, within-class scatter, between-class scatter

中图分类号:

TP181

Wu Qing, Fu Yanlin, Fan Jiulun, Ma Tianlu. Structural regularized twin support vector machine based on within-class scatter and between-class scatter[J]. The Journal of China Universities of Posts and Telecommunications, 2021, 28(4): 39-52.

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Structural regularized twin support vector machine based on within-class scatter and between-class scatter

Structural regularized twin support vector machine based on within-class scatter and between-class scatter

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