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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
Source PublicationNEUROCOMPUTING
2008-10-01
Volume71Issue:16-18Pages:3211-3215
SubtypeArticle
AbstractThe 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.
KeywordLeast-squares Support Vector Machines Parameter Selection Particle Swarm Optimization Classification
WOS HeadingsScience & Technology ; Technology
WOS KeywordSUPPORT VECTOR MACHINE ; LEAST-SQUARES ; MODEL SELECTION ; GENETIC ALGORITHMS ; CLASSIFICATION ; REGRESSION ; BOUNDS ; CLASSIFIERS ; KERNELS ; LSSVM
Indexed ByISTP ; SCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:000260066100020
Citation statistics
Cited Times:96[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/9558
Collection09年以前成果
Affiliation1.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
Recommended Citation
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.
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