Rule induction methods with hierachical sampling

This paper proposes a method for hiearchical sampling for rule induction. The method generates training samples and test samples in a two-level hierarchical way, and compared the results between these two levels, which corresponding to second-order approximation of estimators in Edgeworth expansion. We applied this method to three medical datasets. The results show that this method gives better performance than conventional methods.