Weighted linear loss multiple birth support vector machine based on information granulation for multi-class classification

doi:10.1016/j.patcog.2017.02.011

	Weighted linear loss multiple birth support vector machine based on information granulation for multi-class classification
	Ding, Shifei 1,2; Zhang, Xiekai 1; An, Yuexuan 1; Xue, Yu 3
	2017-07-01
发表期刊	PATTERN RECOGNITION
ISSN	0031-3203
卷号	67 页码:32-46
摘要	Recently proposed weighted linear loss twin support vector machine (WLTSVM) is an efficient algorithm for binary classification. However, the performance of multiple WLTSVM classifier needs improvement since it uses the strategy 'one-versus-rest' with high computational complexity. This paper presents a weighted linear loss multiple birth support vector machine based on information granulation (WLMSVM) to enhance the performance of multiple WLTSVM. Inspired by granular computing, WLMSVM divides the data into several granules and builds a set of sub-classifiers in the mixed granules. By introducing the weighted linear loss, the proposed approach only needs to solve simple linear equations. Moreover, since WLMSVM uses the strategy "all-versus-one" which is the key idea of multiple birth support vector machine, the overall computational complexity of WLMSVM is lower than that of multiple WLTSVM. The effectiveness of the proposed approach is demonstrated by experimental results on artificial datasets and benchmark datasets. (C) 2017 Elsevier Ltd. All rights reserved.
关键词	Multi-class classification Twin support vector machine Multiple birth support vector machine Granular computing
DOI	10.1016/j.patcog.2017.02.011
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61379101] ; National Natural Science Foundation of China[61672522] ; National Key Basic Research Program of China[2013CB329502] ; Priority Academic Program Development of Jiangsu Higer Education Institutions(PAPD) ; Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology(CICAEET)
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号	WOS:000399520700004
出版者	ELSEVIER SCI LTD
引用统计	被引频次：71[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/7254
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Ding, Shifei
作者单位	1.China Univ Min & Technol, Sch Comp Sci & Technol, Xuzhou 221116, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China 3.Nanjing Univ Informat Sci & Technol, Sch Comp & Software, Nanjing 210044, Jiangsu, Peoples R China
推荐引用方式 GB/T 7714	Ding, Shifei,Zhang, Xiekai,An, Yuexuan,et al. Weighted linear loss multiple birth support vector machine based on information granulation for multi-class classification[J]. PATTERN RECOGNITION,2017,67:32-46.
APA	Ding, Shifei,Zhang, Xiekai,An, Yuexuan,&Xue, Yu.(2017).Weighted linear loss multiple birth support vector machine based on information granulation for multi-class classification.PATTERN RECOGNITION,67,32-46.
MLA	Ding, Shifei,et al."Weighted linear loss multiple birth support vector machine based on information granulation for multi-class classification".PATTERN RECOGNITION 67(2017):32-46.