A novel LS-SVMs hyper-parameter selection based on particle swarm optimization

CASIA OpenIR > 09年以前成果

	A novel LS-SVMs hyper-parameter selection based on particle swarm optimization
	Guo, X. C.1,2; Yang, J. H.1; Wu, C. G.1,3; Wang, C. Y.1; Liang, Y. C.1
发表期刊	NEUROCOMPUTING
	2008-10-01
卷号	71 期号:16-18 页码:3211-3215
文章类型	Article
摘要	The selection of hyper-parameters plays an important role to the performance of least-squares support vector machines (LS-SVMs). In this paper, a novel hyper-parameter selection method for LS-SVMs is presented based on the particle swarm optimization (PSO). The proposed method does not need any priori knowledge on the analytic property of the generalization performance measure and can be used to determine multiple hyper-parameters at the same time. The feasibility of this method is examined on benchmark data sets. Different kinds of kernel families are investigated by using the proposed method. Experimental results show that the best or quasi-best test performance could be obtained by using the scaling radial basis kernel function (SRBF) and RBF kernel functions, respectively. (C) 2008 Elsevier B.V. All rights reserved.
关键词	Least-squares Support Vector Machines Parameter Selection Particle Swarm Optimization Classification
WOS标题词	Science & Technology ; Technology
关键词[WOS]	SUPPORT VECTOR MACHINE ; LEAST-SQUARES ; MODEL SELECTION ; GENETIC ALGORITHMS ; CLASSIFICATION ; REGRESSION ; BOUNDS ; CLASSIFIERS ; KERNELS ; LSSVM
收录类别	ISTP ; SCI
语种	英语
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000260066100020
引用统计	被引频次：149[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/9608
专题	09年以前成果
作者单位	1.Jilin Univ, Coll Comp Sci & Technol, Key Lab Symbol Computat & Knowledge Engn, Minist Educ, Changchun 130012, Peoples R China 2.NE Dianli Univ, Coll Sci, Jilin 132012, Peoples R China 3.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100080, Peoples R China
推荐引用方式 GB/T 7714	Guo, X. C.,Yang, J. H.,Wu, C. G.,et al. A novel LS-SVMs hyper-parameter selection based on particle swarm optimization[J]. NEUROCOMPUTING,2008,71(16-18):3211-3215.
APA	Guo, X. C.,Yang, J. H.,Wu, C. G.,Wang, C. Y.,&Liang, Y. C..(2008).A novel LS-SVMs hyper-parameter selection based on particle swarm optimization.NEUROCOMPUTING,71(16-18),3211-3215.
MLA	Guo, X. C.,et al."A novel LS-SVMs hyper-parameter selection based on particle swarm optimization".NEUROCOMPUTING 71.16-18(2008):3211-3215.