SVQR with asymmetric quadratic loss function

- Journal title : Journal of the Korean Data and Information Science Society
- Volume 26, Issue 6, 2015, pp.1537-1545
- Publisher : Korean Data and Information Science Society
- DOI : 10.7465/jkdi.2015.26.6.1537

Title & Authors

SVQR with asymmetric quadratic loss function

Shim, Jooyong; Kim, Malsuk; Seok, Kyungha;

Shim, Jooyong; Kim, Malsuk; Seok, Kyungha;

Abstract

Support vector quantile regression (SVQR) can be obtained by applying support vector machine with a check function instead of an e-insensitive loss function into the quantile regression, which still requires to solve a quadratic program (QP) problem which is time and memory expensive. In this paper we propose an SVQR whose objective function is composed of an asymmetric quadratic loss function. The proposed method overcomes the weak point of the SVQR with the check function. We use the iterative procedure to solve the objective problem. Furthermore, we introduce the generalized cross validation function to select the hyper-parameters which affect the performance of SVQR. Experimental results are then presented, which illustrate the performance of proposed SVQR.

Keywords

Asymmetric quadratic loss function;generalized cross validation;

Language

English

Cited by

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