DocumentCode
2850142
Title
Value reduction in rough sets based on Apriori algorithm
Author
Ma, Yuliang ; Luo, Zhizeng
Author_Institution
Sch. of Autom., Hangzhou Dianzi Univ., Hangzhou, China
fYear
2010
fDate
26-28 May 2010
Firstpage
468
Lastpage
471
Abstract
Aiming at value reduction, a kind of RSVR algorithm was presented based on support in association rules via Apriori algorithm. A more effective reduction table can be obtained by deleting those rules with less support according to least support - minsup. The reduction feasibility of this algorithm was achieved by reducing the given decision table. Testing by UCI machine learning database and comparing this algorithm with least value reduction algorithm indicate the validity of RSVR algorithm.
Keywords
decision tables; learning (artificial intelligence); rough set theory; UCI machine learning database; apriori algorithm; association rules; decision table; least value reduction algorithm; reduction table; rough sets; Association rules; Automation; Data analysis; Data mining; Databases; Machine learning; Machine learning algorithms; Partitioning algorithms; Rough sets; Testing; Apriori algorithm; Association rules; Rough sets; Support; Value reduction;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference (CCDC), 2010 Chinese
Conference_Location
Xuzhou
Print_ISBN
978-1-4244-5181-4
Electronic_ISBN
978-1-4244-5182-1
Type
conf
DOI
10.1109/CCDC.2010.5499015
Filename
5499015
Link To Document