DocumentCode :
553048
Title :
Study of algorithm for rule extraction based on rough set theory
Author :
XianWen Luo
Author_Institution :
Inf. Manage. Dept., Southwest Univ., Chongqing, China
Volume :
1
fYear :
2011
fDate :
26-28 July 2011
Firstpage :
343
Lastpage :
346
Abstract :
The main idea of rough set theory is to extract decision rules by attribute reduction and value reduction in the premises of keeping the ability of classification. In this paper, an algorithm on value reduction and for extracting decision rule based on the membership function is proposed. All the decision rules on decision table and the minimal rule set of reduced conditional attribute set without core-valued table would be attained by this algorithm.
Keywords :
decision making; rough set theory; attribute reduction; conditional attribute set; core valued table; decision rule extraction algorithm; decision table; membership function; minimal rule set; rough set theory; value reduction; Algorithm design and analysis; Classification algorithms; Decision making; Knowledge representation; Set theory; Solar energy; Volcanic activity; membership function; rough set; rule extraction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2011 Eighth International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-61284-180-9
Type :
conf
DOI :
10.1109/FSKD.2011.6019567
Filename :
6019567
Link To Document :
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