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The data mining of TCM syndrome diagnostic criteria by the R_Apriori algorithm

机译:R_Apriori算法对中医证候诊断标准的数据挖掘

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As the association rules mining algorithm, Apriori algorithm is gotten a lot of application used for its easy use. However, it often encountered some problem as low mining efficiency, too many invalid rules acquired and the rules of pattern mining disorder. In this paper, an algorithm called R_Apriori which improved from Apriori algorithm is designed for above problems. It is necessary to build syndrome diagnosis criteria of Traditional Chinese Medical for solution it's non-scientificalness of experience medical. With treatment on the elderly virus pneumonia, a series of process including initial null handle, subtraction operation, reducing data dimension. By data mining based on R_Apriori algorithm, syndrome diagnostic criteria of bacterial pneumonia in the elderly were defined. The method of establishment TCM diagnosis criteria has worthy of promotion.
机译:作为关联规则挖掘算法,Apriori算法以其易于使用而得到了广泛的应用。但是,它经常遇到一些问题,例如挖掘效率低,获取的无效规则过多以及模式挖掘无序规则。针对上述问题,本文设计了一种从Apriori算法改进而来的称为R_Apriori的算法。有必要建立中医证候诊断标准,以解决经验医学的非科学性。通过对老年病毒性肺炎的治疗,一系列过程包括初始无效处理,减法运算,减小数据量。通过基于R_Apriori算法的数据挖掘,确定了老年人细菌性肺炎的综合征诊断标准。建立中医诊断标准的方法值得推广。

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