Using an hebbian learning rule for multi-class SVM classifiers

Journal of Computational Neuroscience

Volumn 17, Issue 3, 2004, Pages 271-287

  Viéville, Thierry ^a   Crahay, Sylvie ^a  

^a INRIA   (France)

Author keywords

Biological model; Neuronal classifier; Supervised learning; Vapnik dimension

Indexed keywords

BIOINFORMATICS; CLASSIFICATION (OF INFORMATION);

BIOLOGICAL MODELS; DATA CLASSIFICATION; HEBBIAN LEARNING; HUMAN VISUAL CORTEX; LEARNING RULES; NEURONAL CLASSIFIER; STATISTICAL LEARNING THEORY; SVM CLASSIFIERS; VAPNIK DIMENSION; VISUAL CLASSIFICATION;

COMPUTER ARCHITECTURE;

ALGORITHM; ANALYTICAL ERROR; BIOLOGICAL MODEL; CALIBRATION; CLASSIFICATION; CONTROLLED STUDY; DATA ANALYSIS; LATENT PERIOD; LEARNING; MATHEMATICAL COMPUTING; NONLINEAR SYSTEM; PARAMETRIC TEST; PRIORITY JOURNAL; REVIEW; RISK ASSESSMENT; SIGN LANGUAGE; STATISTICAL ANALYSIS; THEORY; VISUAL CORTEX; VISUAL DISCRIMINATION; VISUAL MEMORY;

EID: 5744232820     PISSN: 09295313     EISSN: None     Source Type: Journal    
DOI: 10.1023/B:JCNS.0000044873.20850.9c     Document Type: Review

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