DocumentCode
3261299
Title
Attribute reduction among decision tables by voting
Author
Deng, Dayong
Author_Institution
Coll. of Math., Phys. & Inf. Eng., Zhejiang Normal Univ., Jinhua
fYear
2008
fDate
26-28 Aug. 2008
Firstpage
183
Lastpage
187
Abstract
In the paper, we propose a novel method of attribute reduction among decision tables by voting. Different from almost all of other methods of attribute reduction, the method is at higher level of granularity. Its granularity is decision tables but not equivalence classes. The method could be applied into the cases of tremendously large data and dynamical data.
Keywords
data mining; data reduction; decision tables; rough set theory; very large databases; attribute reduction; decision table granularity; dynamical database; large database; rough set theory; voting theory; Concurrent computing; Databases; Distributed computing; Educational institutions; Information systems; Mathematics; Physics; Rough sets; Set theory; Voting;
fLanguage
English
Publisher
ieee
Conference_Titel
Granular Computing, 2008. GrC 2008. IEEE International Conference on
Conference_Location
Hangzhou
Print_ISBN
978-1-4244-2512-9
Electronic_ISBN
978-1-4244-2513-6
Type
conf
DOI
10.1109/GRC.2008.4664669
Filename
4664669
Link To Document