Instance-Based penalization techniques for classification

Georgi Nalbantov, Cor Bioch and Patrick Groenen ()

No EI 2007-01, Econometric Institute Research Papers from Erasmus University Rotterdam, Erasmus School of Economics (ESE), 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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