A Statistical Generation Method of Association Rules by Inference of Diagnostic Test Index in Data Mining

• 발행기관: 한국자료분석학회
• 저자명: 박희창(Hee-Chang Park)
• 간행물 정보: 『Journal of The Korean Data Analysis Society (JKDAS)』Vol.23 No.5, 1997~2010쪽, 전체 14쪽
• 주제분류: 자연과학 > 통계학
• 파일형태: PDF
• 발행일자: 2021.10.30

영문 초록

In this paper, we investigated the possibility of using Youden s index, which is a diagnostic test index used in diagnostic medicine, as an interestingness measure among objective thresholds in association rules. First, we looked at the relationship of confidence measures for the sensitivity and specificity that constitute the Youden index. We also examined the relationship between Youden index and confidence measures by expressing the Youden index formula using various types of confidence, and presented the confidence interval of the Youden index. In addition, after grasping the meaningful properties as interestingness measure, we proved whether the condition of interestingness measure proposed by Piatetsky-Shapiro (1991) was satisfied. By simulation study, if the lower limit of the Youden index has a positive value, it is concluded that there is a positive association rule. If the upper limit of the Youden index has a negative value, it is determined that there is a negative association. If the lower limit of the Youden index has a negative value but the upper limit is positive, then it would be desirable to reserve whether or not there is a association rule.

목차

1. Introduction

2. Diagnostic test tools and index

3. Evaluation of association rule by diagnostic test index

4. Discussion by simulation data

5. Conclusion

References

키워드

association rule confidence diagnostic test index diagnostic test too