A Score Decidability Index for Dynamic Score Combination

In two-class problems, the combination of the outputs (scores) of an ensemble of classifiers is widely used to attain high performance. Dynamic combination techniques that estimate the combination parameters on a pattern per pattern basis, usually provide better performance than those of static combination techniques. In this paper, we propose an Index of Decidability derived from the Wilcoxon-Mann-Whitney statistic, that is used to estimate the combination parameters. Reported results on a multimodal biometric dataset show the effectiveness of the proposed dynamic combination mechanisms in terms of misclassification errors.