원문정보
보안공학연구지원센터(IJHIT)
International Journal of Hybrid Information Technology
Vol.8 No.4
2015.04
pp.193-200
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
In this study, we used three popular data mining techniques (decision trees, artificial neural networks and support vector machine) to analyze the risk factors of medical expense of patients with hepatitis A in Guangdong Province in 2008. We compared the three methods to find out an effective method to predict medical expense and extract main influence factors of the medical expense. The results showed that support vector machine is the most accurate predictor.
목차
Abstract
1. Introduction
2. Previous Research
3. Research Method
3.1. Data Understanding and Data Preparation
3.2. Methods
3.3. Models and Results
4. Conclusion
References
1. Introduction
2. Previous Research
3. Research Method
3.1. Data Understanding and Data Preparation
3.2. Methods
3.3. Models and Results
4. Conclusion
References
저자정보
참고문헌
자료제공 : 네이버학술정보