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Association Rules Mining of Traditional Chinese Medical Syndrome Differentiation Oriented

机译:协会规则挖掘传统中国医学综合征分化导向

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The paper expounds the association rules mining procedure on Traditional Chinese Medical Syndrome Differentiation (TCMSD), comes down to a method - Apriori algorithm which creates the frequent item sets. In the process of creating the frequent item sets, the efficiency of execution becomes lower rapidly as dimensions increasing, so DFP-growth algorithm is provided on the FP-growth algorithm. DFP-growth has the same structure as FP-tree, and makes use of a top-down increment strategy to obtain the frequent item sets.
机译:本文阐述了协会规则采矿程序对传统的中国医学综合征分化(TCMSD),归结为一种方法 - APRiori算法,它创建了频繁的项目集。在创建频繁项目集的过程中,随着尺寸的增加,执行效率随着尺寸的增加而变得越来越亮,因此在FP-生长算法上提供了DFP-生长算法。 DFP-Grange具有与FP-Tree相同的结构,并利用自上而下的增量策略来获得频繁的项目集。

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