The main function of Chinese medicine decision support system is to cluster Chinese medicines based on K-means (cluster Chinese medicines with similar properties into groups, so as to discover new properties of Chinese medicines, which can be referred to during drug use). The other is to classify Chinese medicines by Bayesian classification. The purpose of classification is to find the traditional Chinese medicine that can be used as nutritious food, or to find the traditional Chinese medicine with food and nutritional properties. Firstly, the traditional Chinese medicine with known food properties is used as the sample, and the Bayesian algorithm is used for learning and training. Then, the training model is used to analyze the new traditional Chinese medicine, so as to analyze whether a certain traditional Chinese medicine has the properties of nutritional food. Other functions include traditional Chinese medicine basic information management, traditional Chinese medicine data collection, traditional Chinese medicine data preprocessing, etc. After the operation of classification and clustering, the input data of traditional Chinese medicine will have more predictive values (mainly whether it has food nutrition or which traditional Chinese medicine can be divided into the same group), which can be used for reference by traditional Chinese medicine practitioners.
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