Applied Sciences (Apr 2019)

Research on Classification of Tibetan Medical Syndrome in Chronic Atrophic Gastritis

  • Xiaolan Zhu,
  • Lei Zhang,
  • Yuan Zhang,
  • Lu Wang,
  • Shiying Wang,
  • Ping Liu

DOI
https://doi.org/10.3390/app9081664
Journal volume & issue
Vol. 9, no. 8
p. 1664

Abstract

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Classification association rules that integrate association rules with classification are playing an important role in data mining. However, the time cost on constructing the classification model, and predicting new instances, will be long, due to the large number of rules generated during the mining of association rules, which also will result in the large system consumption. Therefore, this paper proposed a classification model based on atomic classification association rules, and applied it to construct the classification model of a Tibetan medical syndrome for the common plateau disease called Chronic Atrophic Gastritis. Firstly, introduce the idea of “relative support„, and use the constraint-based Apriori algorithm to mine the strong atomic classification association rules between symptoms and syndrome, and the knowledge base of Tibetan medical clinics will be constructed. Secondly, build the classification model of the Tibetan medical syndrome after pruning and prioritizing rules, and the idea of “partial classification„ and “first easy to post difficult„ strategy are introduced to realize the prediction of this Tibetan medical syndrome. Finally, validate the effectiveness of the classification model, and compare with the CBA algorithm and four traditional classification algorithms. The experimental results showed that the proposed method can realize the construction and classification of the classification model of the Tibetan medical syndrome in a shorter time, with fewer but more understandable rules, while ensuring a higher accuracy with 92.8%.

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