Fuzzy particle swarm optimization (FPSO) based feature selection and hybrid kernel distance based possibilistic fuzzy local information C-means (HKD-PFLICM) clustering for churn prediction in telecom industry

被引:0
作者
C. K. Praseeda
B. L. Shivakumar
机构
[1] Bharathiar University,
[2] Sri Ramakrishna College of Arts and Science,undefined
来源
SN Applied Sciences | 2021年 / 3卷
关键词
Customer relationship management (CRM); Churn prediction; Retention; Telecom; Clustering; Classification; Feature selection;
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[1]  
Babu S(2014)A survey on factors impacting churn in telecommunication using datamininig techniques Int J Eng Res Technol (IJERT) 3 1745-1748
[2]  
Ananthanarayanan DN(2012)A customer churn prediction model in telecom industry using boosting IEEE Trans Industr Inf 10 1659-1665
[3]  
Ramesh V(2002)Turning telecommunications call details to churn prediction: a data mining approach Expert Syst Appl 23 103-112
[4]  
Lu N(2016)The perils of proactive churn prevention using plan recommendations: evidence from a field experiment J Mark Res 53 46-60
[5]  
Lin H(2013)Data mining as a tool to predict the churn behaviour among Indian bank customers Int J Recent Innov Trends Comput Commun 1 720-725
[6]  
Lu J(2009)Churn prediction model in retail banking using fuzzy C-means algorithm Informatica 33 1-6
[7]  
Zhang G(2010)Churn models for prepaid customers in the cellular telecommunication industry using large data marts Expert Syst Appl 37 4710-4712
[8]  
Wei CP(2012)Uniformly subsampled ensemble (USE) for churn management: theory and implementation Expert Syst Appl 39 11839-11845
[9]  
Chiu IT(2008)Predicting credit card customer churn in banks using data mining Int J Data Anal Tech Strateg 1 4-28
[10]  
Ascarza E(2007)Computer assisted customer churn management: state-of-the-art and future trends Comput Oper Res 34 2902-2917