Induction of decision tree with fuzzy number-valued attribute
Dongmei Huang, Jie Chi Yang, Xizhao Wang, Ming-Hu Ha · 2004
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.