Regularized Jacobi Wavelets Kernel for Support Vector Machines
AbstractA new family of regularized Jacobi wavelets is constructed. Based on this Jacobi wavelets, a new kernel for support vector machines is presented. Using kernel and frame theory, the Reproducing Kernel Hilbert Space of this kernel is identified. We show that without being a universal kernel, the proposed one possesses a good separation property and a big ability to extract more discriminative features. These theoretical results are confirmed and supported by numerical experiments.
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