Uncertain data classification with additive kernel support vector machine

doi:10.1016/j.datak.2018.07.004

CORC > 国家天文台 > 中国科学院国家天文台

	Uncertain data classification with additive kernel support vector machine
	Xie, Zongxia 1,2,3; Xu, Yong 3; Hu, Qinghua 4
刊名	DATA & KNOWLEDGE ENGINEERING
	2018-09-01
卷号	117 页码:87-97
关键词	Uncertain data Additive kernel Support vector machines Classification
ISSN号	0169-023X
DOI	10.1016/j.datak.2018.07.004
英文摘要	In this work, a classification learning algorithm is designed within the framework of support vector machines through modeling uncertain data with additive kernels, which are introduced to calculate the similarity between uncertain samples characterized by probability density functions (PDFs). The PDFs are used as features of the uncertain samples, where the value of a feature is not a single value, but a set of values that represent the probability distribution of the noise. This is different with the existing methods which represent an uncertain sample by a set of new samples around it, but use the farthest or nearest value in the distribution to construct the optimal hyperplane. With the properties of kernel functions, we can easily extend additive kernels to compute the similarity between samples described with multiple uncertain features. Furthermore, we introduce an efficient algorithm to compute the kernel functions, and solve the additive kernel SVMs. The experimental results show the efficiency of additive-kernel SVMs in uncertain data classification.
资助项目	National Natural Science Foundation of China[61432011] ; National Natural Science Foundation of China[61732011] ; National Natural Science Foundation of China[61105054] ; National Natural Science Foundation of China[61071179] ; National Natural Science Foundation of China[61202259] ; Open Research Program of Key Laboratory of Solar Activity ; China Scholarship Council
WOS关键词	BIG DATA ; RECOGNITION ; INFORMATION
WOS研究方向	Computer Science
语种	英语
出版者	ELSEVIER SCIENCE BV
WOS记录号	WOS:000448496400006
资助机构	National Natural Science Foundation of China ; National Natural Science Foundation of China ; Open Research Program of Key Laboratory of Solar Activity ; Open Research Program of Key Laboratory of Solar Activity ; China Scholarship Council ; China Scholarship Council ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Open Research Program of Key Laboratory of Solar Activity ; Open Research Program of Key Laboratory of Solar Activity ; China Scholarship Council ; China Scholarship Council ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Open Research Program of Key Laboratory of Solar Activity ; Open Research Program of Key Laboratory of Solar Activity ; China Scholarship Council ; China Scholarship Council ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Open Research Program of Key Laboratory of Solar Activity ; Open Research Program of Key Laboratory of Solar Activity ; China Scholarship Council ; China Scholarship Council
内容类型	期刊论文
源URL	[http://ir.bao.ac.cn/handle/114a11/23134]
专题	中国科学院国家天文台
通讯作者	Hu, Qinghua
作者单位	1.Tianjin Univ, Sch Comp Software, Tianjin, Peoples R China 2.Chinese Acad Sci, Natl Astron Observ, Key Lab Solar Act, Beijing 100012, Peoples R China 3.Harbin Inst Technol, Shenzhen Grad Sch, Biocomp Res Ctr, Shenzhen, Peoples R China 4.Tianjin Univ, Sch Comp Sci & Technol, Tianjin, Peoples R China
推荐引用方式 GB/T 7714	Xie, Zongxia,Xu, Yong,Hu, Qinghua. Uncertain data classification with additive kernel support vector machine[J]. DATA & KNOWLEDGE ENGINEERING,2018,117:87-97.
APA	Xie, Zongxia,Xu, Yong,&Hu, Qinghua.(2018).Uncertain data classification with additive kernel support vector machine.DATA & KNOWLEDGE ENGINEERING,117,87-97.
MLA	Xie, Zongxia,et al."Uncertain data classification with additive kernel support vector machine".DATA & KNOWLEDGE ENGINEERING 117(2018):87-97.