Title :
Fuzzy decision tree based on the important degree of fuzzy attribute
Author :
Wang, Xi-Zhao ; Zhai, Jun-hai ; Zhang, Su-fang
Author_Institution :
Coll. of Math. & Comput. Sci., Hebei Univ., Baoding
Abstract :
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.
Keywords :
decision making; decision trees; fuzzy set theory; decision-making; fuzzy attribute degree; fuzzy condition attributes; fuzzy decision tree; fuzzy information system; Computational intelligence; Computer science; Cybernetics; Decision trees; Educational institutions; Fuzzy systems; Information entropy; Information systems; Machine learning; Mathematics; Condition attribute; Decision attribute; Fuzzy attribute; Fuzzy decision tree; Important degree;
Conference_Titel :
Machine Learning and Cybernetics, 2008 International Conference on
Conference_Location :
Kunming
Print_ISBN :
978-1-4244-2095-7
Electronic_ISBN :
978-1-4244-2096-4
DOI :
10.1109/ICMLC.2008.4620458