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中文摘要：
基于是在处理暧昧和不确定性的一个强大的工具的不平的集合理论，到在系统被介绍的不完全的信息和支持和信心的矿协会规则的一个算法被重新定义。没有处理失踪的价值，协会直接与决定属性统治的算法罐头矿。用从 UCI 机器学习仓库的不完全的数据集蘑菇，新算法与古典协会规则采矿算法相比基于从规则的数字自原因推及结果提取、严峻的精确性和实行时间。实验结果证明新算法有短实行时间和高精确性的优点。
英文摘要：
Based on the rough set theory which is a powerful tool in dealing with vagueness and uncertainty, an algorithm to mine association rules in incomplete information systems was presented and the support and confidence were redefined. The algorithm can mine the association rules with decision attributes directly without processing missing values. Using the incomplete dataset Mushroom from UCI machine learning repository, the new algorithm was compared with the classical association rules mining algorithm based on Apriori from the number of rules extracted, testing accuracy and. execution time. The experiment results show that the new algorithm has advantages of short execution time and high accuracy.
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