A Parameter Choosing Method of SVR for Time Series Prediction

被引：0

作者：

Lin, Shukuan ^{[1
]}

Zhang, Shaomin ^{[1
]}

Qiao, Jianzhong ^{[1
]}

Liu, Hualei ^{[1
]}

Yu, Ge ^{[1
]}

机构：

[1] Northeastern Univ, Coll Informat Sci & Engn, Shenyang 110004, Liaoning, Peoples R China

来源：

PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE FOR YOUNG COMPUTER SCIENTISTS, VOLS 1-5 | 2008年

关键词：

Parameter choosing; SVR; time series prediction; improved Cross-Validation; epsilon-weighed;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

It is important to choose good parameters in Support Vector Regression (SVR) modeling. Choosing different parameters will influence the accuracy of SVR models. This paper proposes a parameter choosing method of SVR models for time series prediction. In the light of data features of time series, the paper improves the traditional Cross-Validation method, and combines the improved Cross-Validation with epsilon-weighed SVR in order to get good parameters of models. The experiments show that the method is effective for time series prediction.

引用

页码：130 / 135

页数：6

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