We present distribution independent bounds on the generalization misclassification performance of a family of kernel classifiers with margin. Support Vector Machine classifiers (SVM) stem out of this class of machines. The bounds are derived through computations of the Vγ dimension of a family of loss functions where the SVM one belongs to. Bounds that use functions of margin distributions (i.e. functions of the slack variables of SVM) are derived.
CITATION STYLE
Evgeniou, T., & Pontil, M. (2000). A note on the generalization performance of kernel classifiers with margin. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1968, pp. 306–315). Springer Verlag. https://doi.org/10.1007/3-540-40992-0_23
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