LEM2-Based Rule Induction via Clustering Decision Classes
Masahiro Inuiguchi, D. Fukuda, Masayo Tsurumi, K. Yamanaka · 2006
In this paper, it is proposed to cluster decision classes before applying a rule induction method. The similarity between decision classes is defined and an agglomerative hierarchical clustering method is applied. At each branch of the obtained dendrogram, LEM2, one of frequently used rule induction algorithm, is applied to induce decision rules inferring clusters. In such a way, a set of decision rules classifying objects into decision classes is obtained. The performance of the proposed method is compared with the direct application of LEM2 to each decision class by a numerical experiment.