DocumentCode
3465071
Title
The Study on Rough Set Theory for Customers Churn
Author
Hu, Dengf
Author_Institution
Manage. Sch., Anhui Univ. of Finance & Econ., Bengbu
fYear
2008
fDate
12-14 Oct. 2008
Firstpage
1
Lastpage
4
Abstract
In order to compress or reduce redundant features in customers churn, the rough set theory is introduced and a feature reduction algorithm based on the rough set is proposed. An example in customers churn is given to validate the algorithm. The results show that when the customers churn classification result is almost invariable, the main features which are more important to the churn classification can be searched by this algorithm.
Keywords
customer profiles; feature extraction; pattern classification; rough set theory; customer churn; customers churn classification; feature reduction algorithm; rough set theory; Computational complexity; Data mining; Decision support systems; Economic forecasting; Educational institutions; Finance; Financial management; Inspection; Risk management; Set theory;
fLanguage
English
Publisher
ieee
Conference_Titel
Wireless Communications, Networking and Mobile Computing, 2008. WiCOM '08. 4th International Conference on
Conference_Location
Dalian
Print_ISBN
978-1-4244-2107-7
Electronic_ISBN
978-1-4244-2108-4
Type
conf
DOI
10.1109/WiCom.2008.2194
Filename
4680383
Link To Document