Title :
Rules Mining From Large Datasets Based on Rough Set
Author :
Xiang-gong, Hong ; Zhiyan, Wang ; Sen, Guo ; Ping, Wang
Author_Institution :
Sch. of Inf. Eng., NanChang Univ.
Abstract :
The existing rough set based methods are not applicable for large data sets because of the high time and space complexity. In this paper, a new algorithm, called R_Apriori, is presented by which large data sets are divided into several parts, in combination with a priori algorithm, implicated rules are derived in liner relation to size of data set. At last, this result is proved by experiments based on three classical UCI repositories
Keywords :
data mining; rough set theory; R_Apriori algorithm; data mining; rough set based method; Algorithm design and analysis; Association rules; Computer science; Data engineering; Data mining; Database systems; Information systems; Knowledge representation; Set theory; Space technology;
Conference_Titel :
Communications, Circuits and Systems Proceedings, 2006 International Conference on
Conference_Location :
Guilin
Print_ISBN :
0-7803-9584-0
Electronic_ISBN :
0-7803-9585-9
DOI :
10.1109/ICCCAS.2006.284917
