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The optimal kernel selection is a critical problem for the kernel-based learning algorithm. In order to obtain good results, the kernel function must be chosen in a data-dependent manner. To this end, we propose a new feature space based class separability measure to evaluate the conformation of kernels to the data. The optimal combination coefficients of multiple Gaussian functions are obtained by...
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