Pattern Discovery based on Rule Induction and Taxonomy Generation

Authors:
Shusaku Tsumoto;Shoji Hirano
Affiliations:
-;-
Venue:
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Year:
2003

Citing 5
Cited 0

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Readings in Machine Learning
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Abstract

One of the most important problems with rule inductionmethods is that they cannot extract rules, which plausiblyrepresent experts' decision processes. In this paper,the characteristics of experts' rules are closely examinedand a new approach to extract plausible rules is introduced,which consists of the following three procedures. First, thecharacterization of decision attributes (given classes) is extractedfrom databases and the concept hierarchy for givenclasses is calculated. Second, based on the hierarchy, rulesfor each hierarchical level are induced from data. Then, foreach given class, rules for all the hierarchical levels are integratedinto one rule.