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Advances in Knowledge Discovery and Data Mining

Volume 4426 of the series Lecture Notes in Computer Science pp 355-366

On a New Class of Framelet Kernels for Support Vector Regression and Regularization Networks

  • Wei-Feng ZhangAffiliated withCenter for Computer Vision and Department of Mathematics, Sun Yat-Sen (Zhongshan) University, Guangzhou 510275
  • , Dao-Qing DaiAffiliated withCenter for Computer Vision and Department of Mathematics, Sun Yat-Sen (Zhongshan) University, Guangzhou 510275
  • , Hong YanAffiliated withDepartment of Electronic Engineering, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon

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Abstract

Kernel-based machine learning techniques, such as support vector machines, regularization networks, have been widely used in pattern analysis. Kernel function plays an important role in the design of such learning machines. The choice of an appropriate kernel is critical in order to obtain good performance. This paper presents a new class of kernel functions derived from framelet. Framelet is a wavelet frame constructed via multiresolution analysis, and has both the merit of frame and wavelet. The usefulness of the new kernels is demonstrated through simulation experiments.