DocumentCode :
2310216
Title :
Extended concept of logic minimization for rule reduction
Author :
Intan, Rolly ; Takagi, Noboru
Author_Institution :
Dept. of Inf. Eng., Petra Christian Univ., Surabaya, Indonesia
fYear :
2010
fDate :
18-23 July 2010
Firstpage :
1
Lastpage :
6
Abstract :
Decision table, consists of conditional attributes and decision attribute may be considered as a knowledge representation. Reduction of decision table plays important roles in the process of rule reduction. This paper discusses a process of rule reduction using an extended concept of logic minimization. First, this paper introduces a concept of weighted decision table which is generated from a relational data table. Here, the weighted decision table may have such situation that several similar values of conditional attributes may have correlation to different value of decision attribute with a certain weight. Therefore in the process of rules reduction, it is necessary to extend the concept of logic minimization in order to process such kind of decision table. An algorithm of rule reduction is proposed along with an extended merge operation. During discussion of the proposed concept, some illustrated examples are given to clearly understand the concept.
Keywords :
decision tables; knowledge representation; minimisation; probabilistic logic; conditional attributes; decision attribute; extended merge operation; knowledge representation; logic minimization extended concept; relational data table; rule reduction; weighted decision table; Equations; Mathematical model; Merging; Minimization; Rough sets; Silicon; Software algorithms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems (FUZZ), 2010 IEEE International Conference on
Conference_Location :
Barcelona
ISSN :
1098-7584
Print_ISBN :
978-1-4244-6919-2
Type :
conf
DOI :
10.1109/FUZZY.2010.5584521
Filename :
5584521
Link To Document :
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