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

Volume

1

fYear

2008

fDate

12-15 July 2008

Firstpage

511

Lastpage

516

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/ICMLC.2008.4620458

Filename

4620458