Smoothing Support Vector Machines for e-Insensitive Regressi

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Abstract

Researching smooth support vector machine (SVM) for regression is an active field in data mining. Recently, Lee et al. proposed the smooth SVM for insensitive regression, where smoothing functions play a vital role in smooth SVMs. This paper presents a comparative study on three smooth SVMs: smooth SVM, polynomial smooth SVM and smooth support vector regression. It also discusses promising directions of support vector regression for future work

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