An iterative method for deciding SVM and single layer neural network structures

Neural Processing Letters

Volumn 33, Issue 2, 2011, Pages 171-186

  Hamdani, Tarek M ^a   Alimi, Adel M ^a   Khabou, Mohamed A ^b  

^a UNIVERSITY OF SFAX   (Tunisia)

^b UNIVERSITY OF WEST FLORIDA   (United States)

Author keywords

Beta function; Kernel function; Neural and statistical pattern recognition; Single layer neural network; Support vector machines

Indexed keywords

BETA FUNCTION; DATA POINTS; GENERALIZATION PERFORMANCE; HIDDEN LAYERS; HIDDEN UNITS; ITERATIVE ALGORITHM; KERNEL FUNCTION; NEURAL AND STATISTICAL PATTERN RECOGNITION; NEURAL NETWORK STRUCTURES; NON-LINEARLY SEPARABLE DATA; PERCEPTRON; SINGLE LAYER; SINGLE LAYER NEURAL NETWORK; SINGLE-HIDDEN-LAYER NEURAL NETWORKS; SUPPORT VECTOR; SVM CLASSIFIERS; THRESHOLDING; TRAINING DATA; TWO-CLASS CLASSIFICATION PROBLEMS;

ALGORITHMS; GEARS; ITERATIVE METHODS; NETWORK LAYERS; PATTERN RECOGNITION; SUPPORT VECTOR MACHINES; VECTORS;

NEURAL NETWORKS;

EID: 79956146324     PISSN: 13704621     EISSN: 1573773X     Source Type: Journal    
DOI: 10.1007/s11063-011-9171-3     Document Type: Article

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