Induction of fuzzy decision trees based on fuzzy rough set techniques

Author

Elashiri, Mohamed A. ; Hefny, Hesham A. ; Elwahab, Ashraf H Abd

Author_Institution

Comput. Sci. Dept., Acad. of Specialized Studies, Cairo, Egypt

fYear

2011

fDate

Nov. 29 2011-Dec. 1 2011

Firstpage

134

Lastpage

139

Abstract

Efficient criteria to select fuzzy expanded attributes are important for generation fuzzy decision trees (FDTs). Given a fuzzy information system (FIS), fuzzy expanded attributes play a crucial role in fuzzy decision making. Besides, different fuzzy expanded attributes have different influences on decision making, and some of them may be more important than the others. This paper makes an attempt to improve fuzzy decision tree by extending FDT to the fuzzy rough set theory. One of the main contributions of this paper is a new criterion to select the expanded attributes by using accuracy measure of fuzzy expanded attributes with respect to fuzzy decision attributes.

Keywords

data mining; decision making; decision trees; fuzzy set theory; rough set theory; fuzzy decision making; fuzzy decision trees induction; fuzzy expanded attribute selection; fuzzy information system; fuzzy rough set techniques; Accuracy; Computers; Accuracy measure; Data mining; Fuzzy decision tree; Fuzzy rough set; Fuzzy set; Rough set;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Engineering & Systems (ICCES), 2011 International Conference on

Conference_Location

Cairo

Print_ISBN

978-1-4577-0127-6

Type

conf

DOI

10.1109/ICCES.2011.6141027

Filename

6141027