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Multiclass Universum SVM

08/23/2018
by   Sauptik Dhar, et al.
0

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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