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Determining the kernel and error penalty parameters for support vector machines (SVMs) is very problem-dependent in practice. This paper proposes using a cluster validation index in the feature space to help choose parameters for training 2-norm soft margin support vector machines. With the proposed method, the kernel parameters and the penalty parameter of the error term in the 2-norm soft margin...
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