논문 상세보기
Recently data mining techniques have been used for analysis and classification of data related to industrial accidents. The main objective of this study is to compare performance of algorithms for data analysis of industrial accidents and this paper provides a comparative analysis of 5 kinds of algorithms including CHAID, CART, C4.5, LR (Logistic Regression) and NN (Neural Network) with ROC chart, lift chart and response threshold. In this study, data on 67,278 accidents were analyzed to create risk groups for a number of complications, including the risk of disease and accident. The sample for this work chosen from data related to manufacturing industries during three years (2002~2004) in korea. According to the result analysis, NN has excellent performance for data analysis and classification of industrial accidents.
1. 서론
2. 연구내용 및 방법
2.1 연구 자료
2.2 분석방법
3. 분석결과
3.1 변수 선택
3.2 모델별 결과 비교
4. 결론 및 추후연구
5. 참고문헌
