A Parameter Selection Method for Support Vector Interval Regression Model

Abstract:

Article Preview

The support vector interval regression model is an effective method to estimate imprecise data. Parameters of this model is very important in order to obtain the excellent regression result. The flexible polyhedron search algorithm is a fast optimization algorithm. Based on the flexible polyhedron search algorithm, this paper proposes an automatic parameters selection method for the support vector interval regression model. Experiments illustrate the validity and applicability of the support vector interval regression model based on the flexible polyhedron search algorithm.

Info:

Periodical:

Edited by:

Honghua Tan

Pages:

626-630

DOI:

10.4028/www.scientific.net/AMM.66-68.626

Citation:

Y. Q. Chen "A Parameter Selection Method for Support Vector Interval Regression Model", Applied Mechanics and Materials, Vols. 66-68, pp. 626-630, 2011

Online since:

July 2011

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$35.00

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