Instance-Based penalization techniques for classification

G.. Nalbantov, J.C. Bioch and Patrick Groenen ()

No EI 2007-01 Revision_Date: 2009-07-29, Econometric Institute Report from Erasmus University Rotterdam, Econometric Institute

Abstract: 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.

Date: 2007-01-06

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