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Erschienen in:
2005 | OriginalPaper | Buchkapitel
A New Support Vector Machine for Data Mining
verfasst von : Haoran Zhang, Xiaodong Wang, Changjiang Zhang, Xiuling Xu
Erschienen in: Advanced Data Mining and Applications
Verlag: Springer Berlin Heidelberg
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This paper proposes a new support vector machine (SVM) with a robust loss function for data mining. Its dual optimal formation is also constructed. A gradient based algorithm is designed for fast and simple implementation of the new support vector machine. At the same time it analyzes algorithm’s convergence condition and gives a formula to select learning step size. Numerical simulation results show that the new support vector machine performs significantly better than a standard support vector machine.