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 :
بازگشت