A new local-global approach for classification

Neural Networks

Volumn 23, Issue 7, 2010, Pages 887-891

  Peres, R T ^a   Pedreira, C E ^a  

^a FEDERAL UNIVERSITY OF RIO DE JANEIRO   (Brazil)

Author keywords

Bayes classifier; Classification; Local global; LVQ; Pattern recognition; Prototype; SVM; Vector quantization

Indexed keywords

CLASSIFICATION (OF INFORMATION); FEEDFORWARD NEURAL NETWORKS; NEAREST NEIGHBOR SEARCH; PATTERN RECOGNITION; SUPPORT VECTOR MACHINES; VECTORS;

BAYES CLASSIFIER; CLASSIFICATION METHODS; COMPETITIVE PERFORMANCE; LEARNING VECTOR QUANTIZATION; LOCAL-GLOBAL; PROTOTYPE; UNSUPERVISED ALGORITHMS; UNSUPERVISED APPROACHES;

VECTOR QUANTIZATION;

ALGORITHM; ANALYTIC METHOD; ARTICLE; ARTIFICIAL NEURAL NETWORK; BIOINFORMATICS; FEEDFORWARD NEURAL NETWORK; LAYERED NEURAL NETWORK; LEARNING VECTOR QUANTIZATION; MATHEMATICAL ANALYSIS; MATHEMATICAL MODEL; MATHEMATICAL PARAMETERS; PRIORITY JOURNAL; PROBABILITY; SUPPORT VECTOR MACHINE; ARTIFICIAL INTELLIGENCE; CLUSTER ANALYSIS; STATISTICAL MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CLUSTER ANALYSIS; MODELS, STATISTICAL; NEURAL NETWORKS (COMPUTER);

EID: 77955055117     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neunet.2010.04.010     Document Type: Article

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