Abstract
Association rule is useful to describe knowledge and information extracted from databases. However, a large number of association rules may be extracted. It is difficult for users to understand them. It is reasonable to sum up the rules into a smaller number of rules called representative rules. In this papar, we applied a clustering method to cluster association rules on numeric attribute and proposed an algorithm to generate representative rules from the clusters. We applied our approach to a real database, adult database. As the result, we obtained 124 rules divided into 3 clusters. We compared the rule generating method with another rule selecting method.
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Hashizume, A., Yongguang, B., Du, X., Ishii, N. (2003). Generating Representative from Clusters of Association Rules on Numeric Attributes. In: Liu, J., Cheung, Ym., Yin, H. (eds) Intelligent Data Engineering and Automated Learning. IDEAL 2003. Lecture Notes in Computer Science, vol 2690. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45080-1_82
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DOI: https://doi.org/10.1007/978-3-540-45080-1_82
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