Induction of decision tree with fuzzy number-valued attribute

被引：1

作者：

Huang, DM ^{[1
]}

Yang, R ^{[1
]}

Wang, XZ ^{[1
]}

Ha, MH ^{[1
]}

机构：

[1] Agr Univ Hebei, Coll Sci, Baoding 071001, Peoples R China

来源：

2003 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-5, PROCEEDINGS | 2003年

关键词：

fuzzy number-valued attribute; fuzzy bi-branches decision tree; fuzzy decision tree; comparison extent; degree of truth of fuzzy rules;

D O I：

10.1109/ICMLC.2003.1259721

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

To the learning problems of the triangle type fuzzy number-valued attribute, we present an algorithm regarding the fuzzy number-valued attribute based on the fuzzy information entropy minimization heuristic, this algorithm is used to choose the test attribute and to construct a fuzzy Bi-branches decision tree with comparison extent. By defining comparison extent between a real and a fuzzy number, we can avoid the more lost of information. From the opinion of making strategy, the given algorithm closes to the practice and is effective to deal with fuzzy information.

引用

页码：1446 / 1450

页数：5

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