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Support vector machines (SVMs), initially proposed for two-class classification problems, have been very successful in pattern recognition problems. For multi-class classification problems, the standard hyperplane-based SVMs are made by constructing and combining several hyperplanes. Instead of using maximal-margin hyperplanes, maximal-margin hyperspheres that each tightly encloses all examples from...
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