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Chapter 14 Application Studies of Bayes Discriminant and Cluster in TCM Acupuncture Clinical Data Analysis

机译:第十四章贝叶斯判别和聚类在中医针灸临床数据分析中的应用研究

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For the acupuncture clinical big samples' data, Bayes discriminant method has been studied and applied to determine comprehensive posterior treatment effects of the same disease samples, and a K-mean cluster algorithm with a tolerance value has been proposed and applied to classify the samples based on a transmutative Euclidean distance function which is proposed in this paper. Differences in terms of acupuncture points and posterior treatment effective gradations between pair of samples are originally introduced into an Euclidean distance function. The analysis methods studied in this paper can service scientific analysis on acupuncture clinical data and provide a newest research way to estimate qualities of TCM acupuncture clinical treatment cases presented in the literatures.
机译:对于针灸临床大样本的数据,研究了贝叶斯判别方法并将其用于确定同一疾病样本的综合后处理效果,并提出了一种具有容忍度的K均值聚类算法,并基于该样本对样本进行分类。关于本文提出的变换欧氏距离函数。最初在欧几里得距离函数中引入了一对样本之间在穴位和后处理有效灰度方面的差异。本文研究的分析方法可以为针灸临床资料的科学分析提供依据,并为评估文献中提出的中医针灸临床治疗案例的质量提供最新的研究方法。

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