並列摘要
Association rules discovery is an important database mining algorithm that finds interesting association or correlation relationships among a set of items. One of the well-studied problems in data mining is pruning for association rules in Market Basket Analysis. In this paper, we address the effect of Simpson's Paradox on the decision maker in Market Basket Analysis and proposed a method, called common improvement, to handle Simpson's Paradox in selecting association rules. The proposed method is suited for detecting association rules that are likely to be ignored from the existing methods.
參考文獻
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Megaputer Intelligence Inc.
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