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Churn prediction in telecom using Random Forest and PSO based data balancing in combination with various feature selection strategies
3 references·16 citing·48 second hop
Churn prediction in telecom using Random Forest and PSO based data balancing in combination with various feature selection strategies (2012)Churn prediction in telecom using Random …Customer churn prediction using improved balanced random forests (2008)Customer churn prediction usi…Computer assisted customer churn management: State-of-the-art and future trends (2005)Computer assisted customer ch…A novel evolutionary data mining algorithm with applications to churn prediction (2003)A novel evolutionary data min…Profit-driven weighted classifier with interpretable ability for customer churn prediction (2024)Profit-driven weighted classi…Ensemble Methods in Customer Churn Prediction: A Comparative Analysis of the State-of-the-Art (2023)Ensemble Methods in Customer …Customer retention and churn prediction in the telecommunication industry: a case study on a Danish university (2023)Customer retention and churn …A Swish RNN based customer churn prediction for the telecom industry with a 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(1990)On the Profitability of Long-Life Customers in a Noncontractual Setting: An Empirical Investigation and Implications for Marketing (2000)The Loyalty Effect (2001)Machine learning based customer churn prediction in home appliance rental business (2023)Customer Churn Prediction: A Systematic Review of Recent Advances, Trends, and Challenges in Machine Learning and Deep Learning (2025)A comparison of machine learning techniques for customer churn prediction (2015)A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees (2018)A Churn Prediction Model Using Random Forest: Analysis of Machine Learning Techniques for Churn Prediction and Factor Identification in Telecom Sector (2019)Leveraging metaheuristics with artificial intelligence for customer churn prediction in telecom industries (2023)Predictive Churn Modeling for Sustainable Business in the Telecommunication Industry: Optimized Weighted Ensemble Machine Learning (2023)Ensemble-based deep learning techniques for customer churn prediction model (2024)The Combination of Forecasts (1969)Understanding the Customer Base of Service Providers: An Examination of the Differences between Switchers and Stayers (2000)Enhancing e-commerce customer churn management with a profit- and AUC-focused prescriptive analytics approach (2024)Explainable profit-driven hotel booking cancellation prediction based on heterogeneous stacking-based ensemble classification (2024)Profit-driven fusion framework based on bagging and boosting classifiers for potential purchaser prediction (2024)
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References

  • 2008Customer churn prediction using improved balanced random forests412 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

Cited by

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  • 2022A Swish RNN based customer churn prediction for the telecom industry with a novel feature selection strategy71 cited
  • 2024Profit-driven weighted classifier with interpretable ability for customer churn prediction66 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
  • 2023Ensemble Methods in Customer Churn Prediction: A Comparative Analysis of the State-of-the-Art59 cited
  • 2013Customer attrition in retailing: An application of Multivariate Adaptive Regression Splines51 cited
  • 2018Computing efficient features using rough set theory combined with ensemble classification techniques to improve the customer churn prediction in telecommunication sector

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46 cited
  • 2023Customer retention and churn prediction in the telecommunication industry: a case study on a Danish university42 cited
  • 2020Using Behavioral Analytics to Predict Customer Invoice Payment41 cited
  • 2021Swarm intelligence goal-oriented approach to data-driven innovation in customer churn management40 cited
  • 2013Customer Churn Prediction in Telecommunication A Decade Review and Classification40 cited
  • 2016Late payment prediction models for fair allocation of customer contact lists to call center agents39 cited
  • 2018Current Applications of Machine Learning Techniques in CRM: A Literature Review and Practical Implications37 cited