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- W87821798 abstract "The generalization properties of support vector machines (SVMs) are examined. From a geometrical point of view, the estimated parameter of an SVM is the one nearest the origin in the convex hull formed with given examples. Since introducing soft margins is equivalent to reducing the convex hull of the examples, an SVM with soft margins has a different learning curve from the original. In this paper we derive the asymptotic average generalization error of SVMs with soft margins in simple cases and quantitatively show that soft margins increase the generalization error." @default.
- W87821798 created "2016-06-24" @default.
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- W87821798 date "2004-01-01" @default.
- W87821798 modified "2023-09-25" @default.
- W87821798 title "Effects of Soft Margins on Learning Curves of Support Vector Machines" @default.
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