A New Information Measure Based on Example-Dependent Misclassification Costs and Its Application in Decision Tree Learning

<table>Classifier for dataset NSEP (without costs). Errors of type 1 correspond to misclassifications for both classes occurring in intervals for which a class decision was made. Errors of type 2 correspond to misclassifications in intervals where no confident class decision could be made and the final class was assigned based on a majority decision.</table>

Advances in Artificial Intelligence

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Figure 1

Figure 1: A New Information Measure Based on Example-Dependent Misclassification Costs and Its Application in Decision Tree Learning 