We apply nonsmooth optimization techniques to classification problems, with particular reference to the Transductive Support Vector Machine (TSVM) approach, where the considered decision function is nonconvex and nondifferentiable, hence difficult to minimize. We present some numerical results obtained by running the proposed method on some standard test problems drawn from the binary classification literature.
Nonsmooth optimization techniques for semi-supervised classification
Astorino Annabella;
2007
Abstract
We apply nonsmooth optimization techniques to classification problems, with particular reference to the Transductive Support Vector Machine (TSVM) approach, where the considered decision function is nonconvex and nondifferentiable, hence difficult to minimize. We present some numerical results obtained by running the proposed method on some standard test problems drawn from the binary classification literature.File in questo prodotto:
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