The main objective of this study is to provide feature analysis of industrial accidents in manufacturing industries using CART algorithm, a data mining technique. In this study, data on 10,536 accidents were analyzed to create risk groups, including the risk of disease and accident. Also, this paper used the gains chart produced by the decision tree. According to the result, gains chart can be used for a risk analysis for industrial accidents management. The sample for this work chosen from data related to manufacturing industries during three years (2002～2004) in Korea. The resulting classification rules have been incorporated into development of a developed database tool to help quantify associated risks and act as an early warning system to individual industrial accident in manufacturing industries.

Abstract
 1. 서론
 2. 연구내용 및 방법
  2.1 Decision Tree
  2.2 CART Algorithm
 3. 분석결과
  3.1 데이터 분석
  3.2 이익도표 (Gains Chart) 분석
 4. 특성분석 고찰
 5. 결론 및 추후연구
 6. 참고문헌

• 임영문 | Leem Young Moon
• 황영섭 | Hwang Young Seob