DISTRIBUTIONALLY ROBUST CHANCE CONSTRAINED SVM MODEL WITH l2-WASSERSTEIN DISTANCE

摘要

In this paper, we propose a distributionally robust chanceconstrained SVM model with l(2)-Wasserstein ambiguity. We present equivalent formulations of distributionally robust chance constraints based on l(2)Wasserstein ambiguity. In terms of this method, the distributionally robust chance-constrained SVM model can be transformed into a solvable linear 0-1 mixed integer programming problem when the l(2)-Wasserstein distance is discrete form. The DRCC-SVM model could be transformed into a tractable 0-1 mixed-integer SOCP programming problem for the continuous case. Finally, numerical experiments are given to illustrate the effectiveness and feasibility of our model.

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