PCA-ELM: A robust and pruned extreme learning machine approach based on principal component analysis

Neural Processing Letters

Volumn 37, Issue 3, 2013, Pages 377-392

  Castano A ^a   Fernandez Navarro F ^b   Hervas Martinez C ^c  

^a UNIVERSIDAD DE PINAR DEL RÍO   (Cuba)

^b EUROPEAN SPACE AGENCY   (France)

^c UNIVERSITY OF CÓRDOBA   (Spain)

Author keywords

Classification; Extreme learning machine; Principal component analysis

Indexed keywords

ACTIVATION FUNCTIONS; COMPUTATIONAL COSTS; DETERMINISTIC ALGORITHMS; EXTREME LEARNING MACHINE; FEED-FORWARD NETWORK; PRINCIPAL COMPONENTS ANALYSIS; SLOW CONVERGENCES; UNIVERSAL APPROXIMATORS;

ALGORITHMS; CLASSIFICATION (OF INFORMATION); ITERATIVE METHODS; KNOWLEDGE ACQUISITION; LEARNING SYSTEMS; NETWORK LAYERS;

PRINCIPAL COMPONENT ANALYSIS;

EID: 84878148836     PISSN: 13704621     EISSN: 1573773X     Source Type: Journal    
DOI: 10.1007/s11063-012-9253-x     Document Type: Article

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