Application studies of bayes discriminant and cluster in TCM acupuncture clinical data analysis

Abstract

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. © Springer Science+Business Media Dordrecht 2014.