Rule Induction Via Clustering Decision Classes

  • Yoshifumi Kusunoki
  • Masahiro Inuiguchi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4259)


In this paper, we examine the effects of the application of LEM2 to a hierarchical structure of decision classes. We consider classification problems with multiple decision classes by nominal condition attributes. To such a problem, we first apply an agglomerative hierarchical clustering method to obtain a dendrogram of decision classes, i.e., a hierarchical structure of decision classes. At each branch of the dendrogram, we then apply LEM2 to induce rules inferring a cluster to which an object belongs. A classification system suitable for the proposed rule induction method is designed. By a numerical experiment, we compare the proposed methods with different similarity measure calculations, the standard application of LEM2 and a method with randomly generated dendrogram. As the result, we generally demonstrate the advantages of the proposed method.


Decision Table Rule Induction Standard Application Matching Rule Decision Class 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yoshifumi Kusunoki
    • 1
  • Masahiro Inuiguchi
    • 1
  1. 1.Department of Systems Innovation, Graduate School of Engineering ScienceOsaka UniversityToyonaka, OsakaJapan

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