Adaptive Decision Tree Algorithm for Data Mining in Real-Time Machine Status Database

실시간 기계 상태 데이터베이스에서 데이터 마이닝을 위한 적응형 의사결정 트리 알고리듬

For the last five years, data mining has drawn much attention by researchers and practitioners because of its many applicable domains. This article presents an adaptive decision tree algorithm for dynamically reasoning machine failure cause out of real-time, large-scale machine status database. Among many data mining methods, intelligent decision tree building algorithm is especially of interest in the sense that it enables the automatic generation of decision rules from the tree, facilitating the construction of expert system. On the basis of experiment using semiconductor etching machine, it has been verified that our model outperforms previously proposed decision tree models.