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Instance-Based penalization techniques for classification

Several instance-based large-margin classi¯ers have recently been put forward in the literature: Support Hyperplanes, Nearest Convex Hull classifier, and Soft Nearest Neighbor. We examine those techniques from a common fit-versus-complexity framework and study the links be- tween them. Finally, we compare the performance of these techniques vis-a-vis each other and other standard classification methods.
Year of publication:
2007-01-06
Authors: Groenen, Patrick ; Nalbantov, Nalbantov, G.I. ; Bioch, Bioch, J.C.
Institutions: Faculteit der Economische Wetenschappen, Erasmus Universiteit Rotterdam
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Type of publication: Book / Working Paper
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The text is part of a series RePEc:ems:eureir Number EI 2007-01
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Persistent link: https://www.econbiz.de/10010837721
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