• 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