A multi-output two-stage locally regularized model construction method using the extreme learning machine

Neurocomputing

Volumn 128, Issue , 2014, Pages 104-112

  Du, Dajun ^a,b   Li, Kang ^b   Li, Xue ^a   Fei, Minrui ^a   Wang, Haikuan ^a  

^a SHANGHAI UNIVERSITY   (China)

^b QUEEN'S UNIVERSITY BELFAST   (United Kingdom)

Author keywords

Extreme learning machine; Multi output linear in the parameters (LITP) model; Regularization; Two stage stepwise selection

Indexed keywords

EXTREME LEARNING MACHINE; FAST IMPLEMENTATION; GENERALIZATION CAPABILITY; MULTI-OUTPUT; NON-LINEAR PARAMETERS; REGULARIZATION; TERMINATION CRITERIA; TWO-STAGE STEPWISE SELECTION;

COMPUTATIONAL COMPLEXITY; KNOWLEDGE ACQUISITION; REGRESSION ANALYSIS;

LEARNING SYSTEMS;

ALGORITHM; ARTICLE; CALCULATION; CONTROLLED STUDY; EXTREME LEARNING MACHINE; KERNEL METHOD; MACHINE LEARNING; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; NONLINEAR SYSTEM; PRIORITY JOURNAL; PROCESS OPTIMIZATION; REGRESSION ANALYSIS; SIMULATION;

EID: 84893659522     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2013.03.056     Document Type: Article

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