Neighborhood based sample and feature selection for SVM classification learning

Neurocomputing

Volumn 74, Issue 10, 2011, Pages 1585-1594

  He, Qiang ^a   Xie, Zongxia ^a   Hu, Qinghua ^a   Wu, Congxin ^a  

^a HARBIN INSTITUTE OF TECHNOLOGY   (China)

Author keywords

Feature selection; Neighborhood relation; Rough set; Sample selection; Support vector machine

Indexed keywords

BOUNDARY SAMPLES; CLASSIFICATION ALGORITHM; CLASSIFICATION PERFORMANCE; DECISION BOUNDARY; FEATURE SELECTION; FEATURE SUBSPACE; GENERALIZATION ABILITY; IMPROVING LEARNING; INPUT FEATURES; LEARNING SAMPLES; LEARNING TASKS; NEIGHBORHOOD RELATION; OPTIMAL CLASSIFICATION; POSITIVE REGION; ROUGH SET; ROUGH SET MODELS; SAMPLE SELECTION; SAMPLE SPACE; SUPPORT VECTOR; SVM CLASSIFICATION; TRAINING SAMPLE; TRAINING TIME;

GEARS; ROUGH SET THEORY; SUPPORT VECTOR MACHINES; VECTORS;

FEATURE EXTRACTION;

ALGORITHM; ARTICLE; BOUNDARY SAMPLE; CLASSIFICATION; CONTROLLED STUDY; FEATURE SELECTION; INFORMATION PROCESSING; MACHINE LEARNING; MATHEMATICAL COMPUTING; MATHEMATICAL PHENOMENA; NEIGHBORHOOD BASED ROUGH SET MODEL; PRIORITY JOURNAL; SAMPLING; SUPPORT VECTOR MACHINE;

EID: 79954417238     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2011.01.019     Document Type: Article

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