Title :
A proposal of fuzzy ID3 with ability of learning for AND/OR operators
Author :
Hayashi, Isao ; Ozawa, J.
Author_Institution :
Dept. of Comput. & Ind. Sci., Hannan Univ., Japan
Abstract :
The fuzzy ID3 is a powerful method to acquire fuzzy decision trees. However, the fuzzy ID3 has a couple of problems, i.e., a problem of a lack of representation and an adjusting problem. In our fuzzy ID3, AND/OR operators are formulated using t-norm and t-conorm connectives with parameters and each parameter is adjusted using golden section method. By adjusting parameters, the proposed fuzzy ID3 gives more accurate fuzzy rules for representing the data sets. If t-conorm connective is selected as AND/OR operator, the decision tree has a sub-decision tree
Keywords :
decision theory; fuzzy set theory; knowledge acquisition; learning systems; AND/OR operators; decision tree; fuzzy ID3; fuzzy decision trees; production rules; Decision trees; Entropy; Fuzzy sets; Mutual information; Production; Proposals;
Conference_Titel :
Fuzzy Systems Symposium, 1996. Soft Computing in Intelligent Systems and Information Processing., Proceedings of the 1996 Asian
Conference_Location :
Kenting
Print_ISBN :
0-7803-3687-9
DOI :
10.1109/AFSS.1996.583545
