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An effective hybrid learning system for telecommunication churn prediction
13 references·16 citing·37 second hop
An effective hybrid learning system for telecommunication churn prediction (2013)An effective hybrid learning system for t…Customer churn prediction in telecommunications (2011)Customer churn prediction in …Multi-objective feature selection by using NSGA-II for customer churn prediction in telecommunications (2009)Multi-objective feature selec…Customer churn prediction by hybrid neural networks (2009)Customer churn prediction by …Model of Customer Churn Prediction on Support Vector Machine (2008)Model of Customer Churn Predi…Application of data mining techniques in customer relationship management: A literature review and classification (2008)Application of data mining te…Churn prediction in subscription services: An application of support vector machines while comparing two parameter-selection techniques (2006)Churn prediction in subscript…Predicting customer retention and profitability by using random forests and regression forests techniques (2005)Predicting customer retention…Applying data mining to telecom churn management (2005)Applying data mining to telec…An LTV model and customer segmentation based on customer value: a case study on the wireless telecommunication industry (2003)An LTV model and customer seg…A novel evolutionary data mining algorithm with applications to churn prediction (2003)A novel evolutionary data min…Turning telecommunications call details to churn prediction: a data mining approach (2002)Turning telecommunications ca…Predicting subscriber dissatisfaction and improving retention in the wireless telecommunications industry (2000)Predicting subscriber dissati…Path Analysis: Sociological Examples (1966)Path Analysis: Sociological E…An efficient churn prediction model using gradient boosting machine and metaheuristic optimization (2023)An efficient churn prediction…An adaptive learning approach for customer churn prediction in the telecommunication industry using evolutionary computation and Naïve Bayes (2023)An adaptive learning approach…An Intelligent Hybrid Scheme for Customer Churn Prediction Integrating Clustering and Classification Algorithms (2022)An Intelligent Hybrid Scheme …A Swish RNN based customer churn prediction for the telecom industry with a novel feature selection strategy (2022)A Swish RNN based customer ch…The Effectiveness of Hybrid Learning in Improving of Teacher-Student Relationship in Terms of Learning Motivation (2021)The Effectiveness of Hybrid L…Swarm intelligence goal-oriented approach to data-driven innovation in customer churn management (2021)Swarm intelligence goal-orien…Deep Learning for Customer Churn Prediction in E-Commerce Decision Support (2021)Deep Learning for Customer Ch…Large-scale Ensemble Model for Customer Churn Prediction in Search Ads (2018)Large-scale Ensemble Model fo…Current Applications of Machine Learning Techniques in CRM: A Literature Review and Practical Implications (2018)Current Applications of Machi…Computing efficient features using rough set theory combined with ensemble classification techniques to improve the customer churn prediction in telecommunication sector (2018)Computing efficient features …Intelligent churn prediction for telecom using GP-AdaBoost learning and PSO undersampling (2017)Intelligent churn prediction …Improved credit card churn prediction based on rough clustering and supervised learning techniques (2017)Improved credit card churn pr…Early churn prediction with personalized targeting in mobile social games (2017)Early churn prediction with p…Data-driven agent-based exploration of customer behavior (2017)Data-driven agent-based explo…An efficient system for customer churn prediction through particle swarm optimization based feature selection model with simulated annealing (2017)An efficient system for custo…Intelligent data analysis approaches to churn as a business problem: a survey (2016)Intelligent data analysis app…A Logit Model of Brand Choice Calibrated on Scanner Data (1983)Customer Evaluations of Service Complaint Experiences: Implications for Relationship Marketing (1998)Switching barriers and repurchase intentions in services (2000)Customer churn prediction using improved balanced random forests (2008)Building comprehensible customer churn prediction models with advanced rule induction techniques (2010)Customer Switching Behavior in Service Industries: An Exploratory Study (1995)Forecasting with artificial neural networks: (1998)Churn prediction using comprehensible support vector machine: An analytical CRM application (2014)Customers churn prediction and marketing retention strategies. 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this work references cited by second hop

References

  • 1966Path Analysis: Sociological Examples1,277 cited
  • 2008Application of data mining techniques in customer relationship management: A literature review and classification1,267 cited
  • 2005Applying data mining to telecom churn management514 cited
  • 2002Turning telecommunications call details to churn prediction: a data mining approach460 cited
  • 2006Churn prediction in subscription services: An application of support vector machines while comparing two parameter-selection techniques432 cited
  • 2003An LTV model and customer segmentation based on customer value: a case study on the wireless telecommunication industry411 cited
  • 2003A novel evolutionary data mining algorithm with applications to churn prediction348 cited
  • 2000Predicting subscriber dissatisfaction and improving retention in the wireless telecommunications industry347 cited
  • 2011Customer churn prediction in telecommunications344 cited
  • 2009Customer churn prediction by hybrid neural networks321 cited
  • 2005Predicting customer retention and profitability by using random forests and regression forests techniques308 cited
  • 2008Model of Customer Churn Prediction on Support Vector Machine161 cited
  • 2009Multi-objective feature selection by using NSGA-II for customer churn prediction in telecommunications160 cited

Cited by

  • 2017

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Early churn prediction with personalized targeting in mobile social games
83 cited
  • 2021The Effectiveness of Hybrid Learning in Improving of Teacher-Student Relationship in Terms of Learning Motivation79 cited
  • 2023An adaptive learning approach for customer churn prediction in the telecommunication industry using evolutionary computation and Naïve Bayes76 cited
  • 2016Intelligent data analysis approaches to churn as a business problem: a survey74 cited
  • 2022A Swish RNN based customer churn prediction for the telecom industry with a novel feature selection strategy71 cited
  • 2017An efficient system for customer churn prediction through particle swarm optimization based feature selection model with simulated annealing63 cited
  • 2017Intelligent churn prediction for telecom using GP-AdaBoost learning and PSO undersampling63 cited
  • 2017Improved credit card churn prediction based on rough clustering and supervised learning techniques61 cited
  • 2018Large-scale Ensemble Model for Customer Churn Prediction in Search Ads52 cited
  • 2017Data-driven agent-based exploration of customer behavior47 cited
  • 2018Computing efficient features using rough set theory combined with ensemble classification techniques to improve the customer churn prediction in telecommunication sector46 cited
  • 2022An Intelligent Hybrid Scheme for Customer Churn Prediction Integrating Clustering and Classification Algorithms45 cited
  • 2023An efficient churn prediction model using gradient boosting machine and metaheuristic optimization45 cited
  • 2021Deep Learning for Customer Churn Prediction in E-Commerce Decision Support42 cited
  • 2021Swarm intelligence goal-oriented approach to data-driven innovation in customer churn management40 cited
  • 2018Current Applications of Machine Learning Techniques in CRM: A Literature Review and Practical Implications37 cited