Tuning SVM parameters by using a hybrid CLPSO-BFGS algorithm

Neurocomputing

Volumn 73, Issue 10-12, 2010, Pages 2089-2096

  Li, Shutao ^a   Tan, Mingkui ^a  

^a HUNAN UNIVERSITY   (China)

Author keywords

CLPSO BFGS method; Model selection; Support vector machine

Indexed keywords

BFGS ALGORITHM; BFGS METHOD; BROYDEN-FLETCHER-GOLDFARB-SHANNO; CLPSO-BFGS METHOD; CROSS VALIDATION; GENERALIZATION BOUND; GENERALIZATION ERROR BOUNDS; GRID SEARCH; HYBRID METHOD; HYBRID STRATEGIES; INITIAL VALUES; LOCAL OPTIMA; MULTIPLE PARAMETERS; PARAMETER SETTING; PARTICLE SWARM OPTIMIZERS;

NUMBER THEORY; OPTIMIZATION; SUPPORT VECTOR MACHINES; TUNING;

NUMERICAL METHODS;

ANALYTIC METHOD; ANALYTICAL PARAMETERS; ARTICLE; BROYDEN FLETCHER GOLDFARB SHANNO METHOD; CLASSIFICATION ALGORITHM; COMPREHENSIVE LEARNING PARTICLE SWARM OPTIMIZER; COMPUTER MODEL; MATHEMATICAL COMPUTING; PERFORMANCE MEASUREMENT SYSTEM; PRIORITY JOURNAL; PROCESS OPTIMIZATION; SUPPORT VECTOR MACHINE;

EID: 77952542640     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2010.02.013     Document Type: Article

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