A New Method for Constructing Kernel Function of Support Vector Regression

AN Wen-sen; SUN Yan-guang

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Volume 35 Issue 3

Jun. 2006

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Abstract

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INFORMATION AND CONTROL > 2006 > 35(3): 378-381.

AN Wen-sen, SUN Yan-guang. A New Method for Constructing Kernel Function of Support Vector Regression[J]. INFORMATION AND CONTROL, 2006, 35(3): 378-381.

Citation:

AN Wen-sen, SUN Yan-guang. A New Method for Constructing Kernel Function of Support Vector Regression[J]. INFORMATION AND CONTROL, 2006, 35(3): 378-381.

Citation:

AN Wen-sen, SUN Yan-guang. A New Method for Constructing Kernel Function of Support Vector Regression[J]. INFORMATION AND CONTROL, 2006, 35(3): 378-381.

A New Method for Constructing Kernel Function of Support Vector Regression

AN Wen-sen^1,2,
SUN Yan-guang²

1.
Department of Automation, University of Science and Technology of China, Hefei 230027, China
2.
Automation Research and Design Institute of Metallurgical Industry, Beijing 100071, China

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Received Date: August 10, 2005
Published Date: June 19, 2006

Graphical Abstract

Abstract

Abstract

The principle of support vector regression(SVR)is firstly discussed,then geometry of kernel function is analyzed from the viewpoint of information geometry,and the kernel function is contructed in data-dependent way by a conformal transformation,which reduces volume elements locally in neighborhoods of support vectors in feature space.This makes the performance of SVR improved.Simulation results show the effectiveness of the method.
- support vector machine,
- support vector regression,
- kernel function,
- information geometry

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References (6)

References

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