An Empirical Study of Qualities of Association Rules from a Statistical View Point

Maryann Dorn, Wen-Chi Hou, Dunren Che and Zhewei Jiang
Volume: 4, No: 1, Page: 27 ~ 32, Year: 2008
10.3745/JIPS.2008.4.1.027
Keywords: Data Mining, Association Rule Mining, Rule Evaluation, Chi-square Test
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Abstract
Minimum support and confidence have been used as criteria for generating association rules in all association rule mining algorithms. These criteria have their natural appeals, such as simplicity; few researchers have suspected the quality of generated rules. In this paper, we examine the rules from a more rigorous point of view by conducting statistical tests. Specifically, we use contingency tables and chi-square test to analyze the data. Experimental results show that one third of the association rules derived based on the support and confidence criteria are not significant, that is, the antecedent and consequent of the rules are not correlated. It indicates that minimum support and minimum confidence do not provide adequate discovery of meaningful associations. The chi-square test can be considered as an enhancement or an alternative solution.

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Cite this article
IEEE Style
M. Dorn, W. Hou, D. Che and Z. Jiang, "An Empirical Study of Qualities of Association Rules from a Statistical View Point," Journal of Information Processing Systems, vol. 4, no. 1, pp. 27~32, 2008. DOI: 10.3745/JIPS.2008.4.1.027.

ACM Style
Maryann Dorn, Wen-Chi Hou, Dunren Che, and Zhewei Jiang. 2008. An Empirical Study of Qualities of Association Rules from a Statistical View Point, Journal of Information Processing Systems, 4, 1, (2008), 27~32. DOI: 10.3745/JIPS.2008.4.1.027.