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Rademacher analysis of infimum classifiers AbstractThis paper addresses the problem of analysing the performance of classifiers obtained as the infimum of a set of k weak learners. The main result consists in a bound on the error of these classifiers based on the Rademacher complexity of the weak learners. This theory motivates the development of a classification algorithm called Soft-output Set Cover Machine as an extension of the Set Cover Machine that forms the classifier as a combination of real valued features. The goodness of the Soft-output Set Cover Machine is benchmarked in several real data problems, in comparison with the original Set Cover Machine.
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