Feature selection and parameter optimization for support vector machines: A new approach based on genetic algorithm with feature chromosomes

Expert Systems with Applications

Volumn 38, Issue 5, 2011, Pages 5197-5204

  Zhao, Mingyuan ^a   Fu, Chong ^a   Ji, Luping ^a   Tang, Ke ^a   Zhou, Mingtian ^a  

^a UNIVERSITY OF ELECTRONIC SCIENCE AND TECHNOLOGY OF CHINA   (China)

Author keywords

Feature chromosomes; Feature selection; Genetic algorithm; Parameters optimization; Support vector machines

Indexed keywords

ASYMPTOTIC BEHAVIORS; BENCHMARK DATABASE; CLASSIFICATION ACCURACY; DATA CLASSIFICATION; DIVERSE APPLICATIONS; FEATURE CHROMOSOMES; FEATURE SELECTION; FEATURE SUBSET; FEATURE SUBSET SELECTION; GENERALIZATION ERROR; GRID SEARCH; NEW APPROACHES; PARAMETER OPTIMIZATION; PARAMETER SETTING; PARAMETERS OPTIMIZATION; PROCESSING TIME; REAL-WORLD DATASETS; STRAIGHT LINES; SUPPORT VECTOR; TRAINING PROCEDURES;

CHROMOSOMES; DATA PROCESSING; FEATURE EXTRACTION; GENETIC ALGORITHMS; OPTIMIZATION; PARAMETER ESTIMATION; VECTOR SPACES; VECTORS;

SUPPORT VECTOR MACHINES;

EID: 79151484699     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2010.10.041     Document Type: Article

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