An Improved ID3 Decision Tree Algorithm

摘要：

Decision tree is an important method for both induction research and data mining, which is mainly used for model classification and prediction. ID3 algorithm is the most widely used algorithm in the decision tree so far. Through illustrating on the basic ideas of decision tree in data mining, in this paper, the shortcoming of ID3s inclining to choose attributes with many values is discussed, and then a new decision tree algorithm combining ID3 and Association Function(AF) is presented. The experiment results show that the proposed algorithm can overcome ID3s shortcoming effectively and get more reasonable and effective rules.

关键词： data mining decision tree ID3 association function(AF) variety bias

作者: Chen Jin Luo De-lin Mu Fen-xiang

作者单位: School of Information Science and Technology Xiamen University Xiamen, 361005, China Tsingtao Huanghai Vocational College Tsingtao, 266427, China

会议类型: 国际会议

会议名称: 第四届国际计算机新科技与教育学术会议(2009 4th International Conference on Computer Science & Education)

会议地点: 南京

会议语种:英文

页码: 127-130

在线出版日期: 2009-07-25（万方平台首次上网日期，不代表论文的发表时间）