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Application of Computational Intelligence to Predict Churn and Non-Churn of Customers in Indian Telecommunication
15 references·1 citing·47 second hop
Application of Computational Intelligence to Predict Churn and Non-Churn of Customers in Indian Telecommunication (2015)Application of Computational Intelligence…Behavior-Based Telecommunication Churn Prediction with Neural Network Approach (2011)Behavior-Based Telecommunicat…A Neuro-Fuzzy Classifier for Customer Churn Prediction (2011)A Neuro-Fuzzy Classifier for …Predicting customer churn by integrating the effect of the customer contact network (2010)Predicting customer churn by …Application of fuzzyARTMAP for churn prediction in bank credit cards (2009)Application of fuzzyARTMAP fo…Predicting credit card customer churn in banks using data mining (2008)Predicting credit card custom…TreeLogit Model for Customer Churn Prediction (2006)TreeLogit Model for Customer …Toward a hybrid data mining model for customer retention (2006)Toward a hybrid data mining m…Defection Detection: Measuring and Understanding the Predictive Accuracy of Customer Churn Models (2006)Defection Detection: Measurin…Predicting customer retention and profitability by using random forests and regression forests techniques (2005)Predicting customer retention…Improved customer choice predictions using ensemble methods (2005)Improved customer choice pred…Computer assisted customer churn management: State-of-the-art and future trends (2005)Computer assisted customer ch…Applying data mining to telecom churn management (2005)Applying data mining to telec…A Data Mining Approach for Retailing Bank Customer Attrition Analysis (2004)A Data Mining Approach for Re…A novel evolutionary data mining algorithm with applications to churn prediction (2003)A novel evolutionary data min…Implications of Loyalty Program Membership and Service Experiences for Customer Retention and Value (2000)Implications of Loyalty Progr…A SLR on Customer Dropout Prediction (2022)A SLR on Customer Dropout Pre…A Cognitive Model of the Antecedents and Consequences of Satisfaction Decisions (1980)Zero defections: quality comes to services. 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this work references cited by second hop

References

  • 2000Implications of Loyalty Program Membership and Service Experiences for Customer Retention and Value1,157 cited
  • 2006Defection Detection: Measuring and Understanding the Predictive Accuracy of Customer Churn Models574 cited
  • 2005Applying data mining to telecom churn management514 cited
  • 2003A novel evolutionary data mining algorithm with applications to churn prediction348 cited
  • 2005Computer assisted customer churn management: State-of-the-art and future trends340 cited
  • 2005Predicting customer retention and profitability by using random forests and regression forests techniques308 cited
  • 2008Predicting credit card customer churn in banks using data mining145 cited
  • 2006Toward a hybrid data mining model for customer retention120 cited
  • 2005Improved customer choice predictions using ensemble methods92 cited
  • 2004A Data Mining Approach for Retailing Bank Customer Attrition Analysis80 cited
  • 2011A Neuro-Fuzzy Classifier for Customer Churn Prediction37 cited
  • 2011Behavior-Based Telecommunication Churn Prediction with Neural Network Approach23 cited
  • 2006TreeLogit Model for Customer Churn Prediction23 cited
  • 2010Predicting customer churn by integrating the effect of the customer contact network13 cited

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2009
Application of fuzzyARTMAP for churn prediction in bank credit cards
12 cited

Cited by

  • 2022A SLR on Customer Dropout Prediction8 cited