A Note on Extending Generalization Bounds for Binary Large-Margin Classifiers to Multiple Classes
نویسندگان
چکیده
A generic way to extend generalization bounds for binary large-margin classifiers to large-margin multi-category classifiers is presented. The simple proceeding leads to surprisingly tight bounds showing the same Õ(d) scaling in the number d of classes as state-of-the-art results. The approach is exemplified by extending a textbook bound based on Rademacher complexity, which leads to a multi-class bound depending on the sum of the margin violations of the classifier.
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تاریخ انتشار 2012