Research on Decision Tree Algorithm Based on Information Entropy

摘要：

Decision tree is an important learning method in machine learning and data mining,this paper discusses the method of choosing the best attribute based on information entropy .It analyzes the process and the characters of classification and the discovery knowledge based on decision tree about the application of decision tree on data mining.Through an instance,the paper shows the procedure of selecting the decision attribute in detail,finally it pointes out the developing trends of decision tree.

关键词： decision tree Classification algorithm entropy information gain gain ratio

作者: Wei Ning Yong Liang Yuncheng Wang

作者单位: College of Information Science and Engineering,Shandong Agriculture University.Taian 271018,China

会议类型: 国际会议

会议名称: 中国数学会生物数学分会第六届学术年会

会议地点: 山东泰安

会议语种:英文

页码: 568-572

在线出版日期: 2008-07-25（万方平台首次上网日期，不代表论文的发表时间）