Geometrical modification of wavelet SVM kernels and its application in microarray analysis

Abstract

The selection and design of appropriate kernel functions play a key role in effective support vector machine (SVM) leaning. A general strategy is to customize the existent kernel functions to fit into the data property and structure. Wavelet kernels have been developed to approximate arbitrary nonlinear functions for signal processing. In this paper, we… (More)
DOI: 10.1109/GENSiPS.2011.6169467

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