산업재해 예측 모델링에서 순서형 분류를 위한 순서형 의사 결정 트리 알고리즘의 응용과 한계
Applications and Limitations of Ordered Decision Tree Algorithms for Ordered Classification in Industrial Accident Predictive Modeling
변해원(한국기술교육대학교)
27권 4호, 560~565쪽
초록
This paper reviews ordinal decision tree algorithms for ordinal classification, exploring theoretical foundations, key algorithms (MDT, QMDT), specialized splitting criteria (Ordinal Gini, Weighted Information Gain), and ensemble methods. It discusses applications in healthcare and social sciences, highlighting interpretability and flexibility while acknowledging overfitting and instability. As implications for future research, this study points out advantages such as interpretability and flexibility, and limitations such as overfitting and instability.
Abstract
This paper reviews ordinal decision tree algorithms for ordinal classification, exploring theoretical foundations, key algorithms (MDT, QMDT), specialized splitting criteria (Ordinal Gini, Weighted Information Gain), and ensemble methods. It discusses applications in healthcare and social sciences, highlighting interpretability and flexibility while acknowledging overfitting and instability. As implications for future research, this study points out advantages such as interpretability and flexibility, and limitations such as overfitting and instability.
- 발행기관:
- 한국기계항공기술학회
- 분류:
- 기계공학