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Publikācija: A Comparison of Heuristic Methods for Polynomial Regression Model Induction

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Nosaukums oriģinālvalodā A Comparison of Heuristic Methods for Polynomial Regression Model Induction
Pētniecības nozare 1. Dabaszinātnes
Pētniecības apakšnozare 1.2. Datorzinātne un informātika
Autori Gints Jēkabsons
Jurijs Lavendels
Atslēgas vārdi Polynomial regression, model selection, heuristic search, state space
Anotācija We compare four different heuristic methods for polynomial regression model induction. The methods are very different in their approaches. Our main concern in this study is in the differences of candidate model spaces the methods deal with (completely predefined versus non-predefined), as well as search strategies used. We investigate the advantages and disadvantages of the approaches represented by the methods in terms of predictive error, complexity of the induced models and required computational resources. For empirical comparisons, we use twelve test problems.
DOI: 10.3846/1392-6292.2008.13.17-27
Hipersaite: http://www.tandfonline.com/doi/abs/10.3846/1392-6292.2008.13.17-27#.U39bWLeKC1s 
Atsauce Jēkabsons, G., Lavendels, J. A Comparison of Heuristic Methods for Polynomial Regression Model Induction. Mathematical Modelling and Analysis, 2008, Vol.13, No.1, 17.-27.lpp. ISSN 1392-6292. e-ISSN 1648-3510. Pieejams: doi:10.3846/1392-6292.2008.13.17-27
ID 3041