한국한의학연구원논문집 (Korean Journal of Oriental Medicine)

한국한의학연구원 (Korean Institute of Oriental Medicine)
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사상체질 임상자료 기반 의사결정나무 생성 알고리즘 비교

Comparison among Algorithms for Decision Tree based on Sasang Constitutional Clinical Data

  • 진희정 (한국한의학연구원) ;
  • 이수경 (원광대학교 한의과대학 한방재활의학과) ;
  • 이시우 (한국한의학연구원)
  • Jin, Hee-Jeong (Korea Institute of Oriental Medicine) ;
  • Lee, Su-Kyung (Dept. of Oriental Rehabilitation, Wonkwang University School of Oriental Medicine) ;
  • Lee, Si-Woo (Korea Institute of Oriental Medicine)
  • 투고 : 2011.06.30
  • 심사 : 2011.08.03
  • 발행 : 2011.08.30
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초록

Objectives : In the clinical field, it is important to understand the factors that have effects on a certain disease or symptom. For this, many researchers apply Data Mining method to the clinical data that they have collected. One of the efficient methods for Data Mining is decision tree induction. Many researchers have studied to find the best split criteria of decision tree; however, various split criteria coexist. Methods : In this paper, we applied several split criteria(Information Gain, Gini Index, Chi-Square) to Sasang constitutional clinical information and compared each decision tree in order to find optimal split criteria. Results & Conclusion : We found BMI and body measurement factors are important factors to Sasang constitution by analyzing produced decision trees with different split measures. And the decision tree using information gain had the highest accuracy. However, the decision tree that produced highest accuracy is changed depending on given data. So, researcher have to try to find proper split criteria for given data by understanding attribute of the given data.

키워드

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