THE DATA MINING METHOD BASED ON SECOND LEARNING

摘要：

Decision tree algorithm is not only the important part of machine learning, but also the most widely used data mining tool. At present, there are many algorithms of generating decision tree, but when the database which we rely on exists noise, high quality knowledge is hard to obtain by 103 algorithm. In this paper, we propose the data mining method based on second learning in case of ID3 algorithm, and analyze the performance of our method by a concrete database. Theory analysis and simulation indicate that this method posses the feature of strong operability, and it can improve the reliability of obtained knowledge.

关键词： Decision tree ID3 algorithm Noise Second learning Accuracy rate

作者: YAN LI GUO-GANG LI FA-CHAO LI CHEN-XIA JIN

作者单位: School of Science, Hebei University of Science and Technology, Shijiazhuang 050018, China School of Economy and Management, Hebei University of Science and Technology, Shijiazhuang 050018, C

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 340-344

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）