基于最小最小基本规则的关联规则集结构

Tin C. Truong, Anh N. Tran, Thong Tran
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引用次数: 6

摘要

本文将关联规则集划分为不相交的等价规则类。每个规则集包含具有相同置信度的规则,然后根据规则集上的顺序关系划分为基本规则集和结果规则集。基本规则集是根据这种关系包含最小元素的基本规则集,它由我们的算法MG_BARS直接找到。此外,通过在MG_CARS算法的基本规则两侧添加适当的可消除项集,可以完整地、不重复地生成结果规则,并保持置信度。实验结果证明了上述算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Structure of Association Rule Set Based on Min-Min Basic Rules
In this paper, we partition the association rule set into disjoint equivalence rule classes. Each of them contains rules having the same confidence and then it is split into basic and consequence rule sets based on the order relation on it. Basic rule set, which includes minimal elements according to this relation, is directly found by our algorithm MG_BARS. In addition, by adding appropriate eliminable itemsets to both sides of basic rules in our algorithm MG_CARS, the consequence rules are completely and non-repeatedly generated and are confidence-preserved. Results of the experiments proved the efficiency of the above algorithms.
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