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arXiv · 1808.08111

Multiclass Universum SVM

Sauptik Dhar·Vladimir Cherkassky·Mohak Shah
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Abstract

We introduce Universum learning for multiclass problems and propose a novel formulation for multiclass universum SVM (MU-SVM). We also propose an analytic span bound for model selection with almost 2-4x faster computation times than standard resampling techniques. We empirically demonstrate the efficacy of the proposed MUSVM formulation on several real world datasets achieving > 20% improvement in test accuracies compared to multi-class SVM.

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Sauptik Dhar, Vladimir Cherkassky, Mohak Shah. 2018-08-23. Multiclass Universum SVM. https://arxiv.org/abs/1808.08111

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