Nu-support Vector Machine as Conditional Value-at-risk Minimization

Abstract

The ν-support vector classification (ν-SVC) algorithm was shown to work well and provide intuitive interpretations, e.g., the parameter ν roughly specifies the fraction of support vectors. Although ν corresponds to a fraction, it cannot take the entire range between 0 and 1 in its original form. This problem was settled by a non-convex extension of ν-SVC… (More)
DOI: 10.1145/1390156.1390289

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