(太原理工大学 计算机与软件学院, 太原 030024)
关键词:代表性数据; 决策树; 聚类; 围绕中心点的划分; 集成学习; Bagging; Boosting
Ensemble of decision trees based on representative data
LI Haifang, DING Zhoufang, WANG Liqun
(College of Computer & Software, Taiyuan University of Technology, Taiyuan 030024, China)
To generate better ensemble output of decision trees, based on the theoretic analysis, this paper put forward a method used for ensemble of decision trees with representative data from the data point of view .This method extracted representative data via partition around medoids (PAM) algorithm from the original training set at first, then it trained a number of decision trees with the help of the representative data and built a ensemble model with the trained decision trees. This method could select the less representative data and trained the better ensemble model of decision trees. The experiment results show that this method can obtain higher ensemble precision of decision trees than Bagging or Boosting furthermore it uses less representative training set. ......