Multiple surrogates: How cross-validation errors can help us to obtain the best predictor

Structural and Multidisciplinary Optimization

Volumn 39, Issue 4, 2009, Pages 439-457

  Viana, Felipe A C ^a   Haftka, Raphael T ^a   Steffen Jr , Valder ^b  

^a University of Florida   (United States)

^b FEDERAL UNIVERSITY OF UBERLÂNDIA   (Brazil)

Author keywords

Cross validation errors; Multiple surrogate models; Prediction sum of squares; Weighted average surrogates

Indexed keywords

CROSS VALIDATION; CROSS-VALIDATION ERRORS; ENGINEERING PROBLEMS; HIGH DIMENSIONS; INTEGRATED SQUARE ERRORS; LEAVE-ONE-OUT; MULTIPLE SURROGATE MODELS; PREDICTION SUM OF SQUARES; RMS ERRORS; SURROGATE MODEL; WEIGHTED AVERAGE SURROGATES; WEIGHTED AVERAGES; WEIGHTING SCHEME;

ERRORS; MODELS;

PRESSES (MACHINE TOOLS);

EID: 69949172900     PISSN: 1615147X     EISSN: 16151488     Source Type: Journal    
DOI: 10.1007/s00158-008-0338-0     Document Type: Article

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