DocumentCode
2150542
Title
Finding Value Reducts Using Rough Multisets
Author
Chan, Chien-Chung ; Chen, Chen ; Garikapati, Varundev
Author_Institution
Dept. of Comput. Sci., Univ. of Akron, Akron, OH, USA
fYear
2010
fDate
14-16 Aug. 2010
Firstpage
85
Lastpage
89
Abstract
This paper introduces a new value reduction algorithm for generating rules from consistent and inconsistent examples represented by Multiset Decision Tables (MDT). The algorithm is implemented as stored procedure in MS SQL, hence, it is capable of dealing with very large data sets. The running time of value reduction algorithm is higher than the decision tree program, in general. However, by using a minimum support threshold, the run-time can be improved significantly as indicated in our experiments using the IDS data set of 4 million records.
Keywords
SQL; data reduction; decision tables; decision trees; rough set theory; IDS data; MS SQL; decision tree program; multiset decision tables; rough multisets; value reduction algorithm; Approximation methods; Decision trees; Finite element methods; Information systems; Partitioning algorithms; Rough sets;
fLanguage
English
Publisher
ieee
Conference_Titel
Granular Computing (GrC), 2010 IEEE International Conference on
Conference_Location
San Jose, CA
Print_ISBN
978-1-4244-7964-1
Type
conf
DOI
10.1109/GrC.2010.150
Filename
5576274
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