关键词: 决策树, 模糊集, 模糊增益比例, 聚类

Abstract: The choosing of node attribute is the pivotal tache during the building process of decision tree.ID3 and C4.5 are the representations of classical decision tree arithmetic，in which tree node is chosen by computing the information gain or gain ratio on the basis of the number of subset.However，due to continuity attribute，dispersed partition result in the faintness of subjection of subset boundary element，which makes the method of sample computing illogical.Adopting fuzzy set theory and using the way of fuzzy gain ratio instead of the way of the number of sample participating in plus property computing，this paper presents one feasible method of uncertainty scale in gaining decision tree classification.

Key words: decision tree, fuzzy set, fuzzy gain ratio, clustering