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Support vector classification with Gaussian RBF kernel is sensitive to the kernel width. Small kernel width may cause over-fitting, and large one under-fitting. The so-called optimal kernel width is merely selected based on the tradeoff between under-fitting loss and over-fitting loss. So, there exists urgent need to further reduce the tradeoff loss. To circumvent this, we scale the kernel width in...
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