Economic Growth Prediction Using Optimized Support Vector Machines

Elmira Emsia () and Cagay Coskuner ()
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Elmira Emsia: Islamic Azad University Iran
Cagay Coskuner: Eastern Mediterranean University (EMU)

Computational Economics, 2016, vol. 48, issue 3, No 4, 453-462

Abstract: Abstract The main objective of this research is to propose a new hybrid model called genetic algorithms–support vector regression (GA–SVR). The proposed model consists of three stages. In the first stage, after lag selection, the most efficient features are selected using stepwise regression algorithm (SRA). Afterward, these variables are used in order to develop proposed model, in which the model uses support vector machines that the parameters of which are tuned by GA. Finally, evaluation of the proposed model is carried out by applying it on the test data set.

Keywords: Genetic algorithms; Support vector regression; Stepwise regression algorithm (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s10614-015-9528-1

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