FUZZY DECISION TREE BASED ON THE IMPORTANT DEGREE OF FUZZY ATTRIBUTE

摘要：

There may be many fuzzy attributes in a fuzzy information system. Different fuzzy attribute has different contribution to classification. More important attributes have more contribution than the others to decision-making. In this paper, based on the importance of the fuzzy condition attributes, a new method generating a fuzzy decision tree is proposed, which uses the important degree of the fuzzy condition attribute with respect to the fuzzy decision attributes to select attributes to expand the branches of a fuzzy decision tree. A comparison between the new method and fuzzy ID3 is provided. It is shown that the new method is more efficient than fuzzy ID3.

关键词： Condition attribute Decision attribute Fuzzy attribute Fuzzy decision tree Important degree

作者: XI-ZHAO WANG JUN-HAI ZHAI SU-FANG ZHANG

作者单位: Key Lab.of Machine Learning and Computational Intelligence, College of Mathematics and Computer Scie Teaching and research of section of mathematics, Hebei Information Engineering School, Baoding, 0710

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: 511-516

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）