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Application of Machine Learning in the Telecommunications Industry: Partial Churn Prediction by using a Hybrid Feature Selection Approach
16 references·0 citing·43 second hopsampled
Application of Machine Learning in the Telecommunications Industry: Partial Churn Prediction by using a Hybrid Feature Selection Approach (2023)Application of Machine Learning in the Te…Customer churn prediction in telecom using machine learning in big data platform (2019)Customer churn prediction in …A Churn Prediction Model Using Random Forest: Analysis of Machine Learning Techniques for Churn Prediction and Factor Identification in Telecom Sector (2019)A Churn Prediction Model Usin…A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees (2018)A new hybrid classification a…Customer churn prediction in the telecommunication sector using a rough set approach (2016)Customer churn prediction in …A comparative analysis of data preparation algorithms for customer churn prediction: A case study in the telecommunication industry (2016)A comparative analysis of dat…A comparison of machine learning techniques for customer churn prediction (2015)A comparison of machine learn…New insights into churn prediction in the telecommunication sector: A profit driven data mining approach (2011)New insights into churn predi…Building comprehensible customer churn prediction models with advanced rule induction techniques (2010)Building comprehensible custo…Customer churn prediction by hybrid neural networks (2009)Customer churn prediction by …Modeling churn using customer lifetime value (2008)Modeling churn using customer…Handling class imbalance in customer churn prediction (2008)Handling class imbalance in c…Customer churn prediction using improved balanced random forests (2008)Customer churn prediction usi…Customer churn analysis: Churn determinants and mediation effects of partial defection in the Korean mobile telecommunications service industry (2006)Customer churn analysis: Chur…Churn prediction in subscription services: An application of support vector machines while comparing two parameter-selection techniques (2006)Churn prediction in subscript…Bagging and Boosting Classification Trees to Predict Churn (2006)Bagging and Boosting Classifi…From Intentions to Actions: A Theory of Planned Behavior (1985)From Intentions to Actions: A…Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research (1975)Self-efficacy: Toward a unifying theory of behavioral change. (1977)Self-efficacy: Toward a unifying theory of behavioral change. (1977)The theory of planned behavior (1991)Understanding Information Technology Usage: A Test of Competing Models (1995)Efficacy of the Theory of Planned Behaviour: A meta‐analytic review (2001)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)Analytics for Customer Engagement (2010)Market Segmentation: Conceptual and Methodological Foundations (1997)Market Segmentation (2000)Customer Metrics and Their Impact on Financial Performance (2006)Creating Enduring Customer Value (2016)Customer satisfaction, customer retention, and market share (1993)The Behavioral Consequences of Service Quality (1996)Understanding the Customer Base of Service Providers: An Examination of the Differences between Switchers and Stayers (2000)Retention Futility: Targeting High-Risk Customers Might be Ineffective (2017)A machine learning framework for customer purchase prediction in the non-contractual setting (2018)Customer base analysis: partial defection of behaviourally loyal clients in a non-contractual FMCG retail setting (2004)Defection Detection: Measuring and Understanding the Predictive Accuracy of Customer Churn Models (2006)Application of machine learning to construction injury prediction (2016)Customer churn prediction system: a machine learning approach (2021)A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)Benchmarking state-of-the-art classification algorithms for credit scoring (2003)Modeling Customer Lifetime Value (2006)Evaluating multiple classifiers for stock price direction prediction (2015)A desicion-theoretic generalization of on-line learning and an application to boosting (1995)Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management (2004)Reshaping the contexts of online customer engagement behavior via artificial intelligence: A conceptual framework (2020)Customer Switching Behavior in Service Industries: An Exploratory Study (1995)Understanding the Effect of Customer Relationship Management Efforts on Customer Retention and Customer Share Development (2003)The Effects of Customer Satisfaction, Relationship Commitment Dimensions, and Triggers on Customer Retention (2005)COVID‐19 Pandemic in the New Era of Big Data Analytics: Methodological Innovations and Future Research Directions (2020)Machine learning for credit scoring: Improving logistic regression with non-linear decision-tree effects (2021)Customer retention, loyalty, and satisfaction in the German mobile cellular telecommunications market (2001)Turning telecommunications call details to churn prediction: a data mining approach (2002)Customer Churn Prediction in Telecom Sector Using Machine Learning Techniques (2022)A Review on Machine Learning Methods for Customer Churn Prediction and Recommendations for Business Practitioners (2024)Zero defections: quality comes to services. (1990)Marketing management: analysis. planning. implementation and control (2000)Data Science in Economics: Comprehensive Review of Advanced Machine Learning and Deep Learning Methods (2020)Integrated Churn Prediction and Customer Segmentation Framework for Telco Business (2021)
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References

  • 1985From Intentions to Actions: A Theory of Planned Behavior20,194 cited
  • 2008Handling class imbalance in customer churn prediction590 cited
  • 2019Customer churn prediction in telecom using machine learning in big data platform576 cited
  • 2018A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees569 cited
  • 2015A comparison of machine learning techniques for customer churn prediction518 cited
  • 2011New insights into churn prediction in the telecommunication sector: A profit driven data mining approach504 cited
  • 2006Churn prediction in subscription services: An application of support vector machines while comparing two parameter-selection techniques453 cited
  • 2019A Churn Prediction Model Using Random Forest: Analysis of Machine Learning Techniques for Churn Prediction and Factor Identification in Telecom Sector448 cited
  • 2008Customer churn prediction using improved balanced random forests434 cited
  • 2006Bagging and Boosting Classification Trees to Predict Churn430 cited
  • 2010Building comprehensible customer churn prediction models with advanced rule induction techniques391 cited
  • 2006Customer churn analysis: Churn determinants and mediation effects of partial defection in the Korean mobile telecommunications service industry339 cited
  • 2009Customer churn prediction by hybrid neural networks336 cited

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  • 2016Customer churn prediction in the telecommunication sector using a rough set approach222 cited
  • 2016A comparative analysis of data preparation algorithms for customer churn prediction: A case study in the telecommunication industry214 cited
  • 2008Modeling churn using customer lifetime value187 cited
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