Support vector machines with a reject option

@inproceedings{Wegkamp2011SupportVM,
  title={Support vector machines with a reject option},
  author={Marten H. Wegkamp and Ming Cheng Yuan},
  year={2011}
}
This paper studies $\ell_1$ regularization with high-dimensional features for support vector machines with a built-in reject option (meaning that the decision of classifying an observation can be withheld at a cost lower than that of misclassification). The procedure can be conveniently implemented as a linear program and computed using standard software. We prove that the minimizer of the penalized population risk favors sparse solutions and show that the behavior of the empirical risk… CONTINUE READING

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