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The Application ofAdaBoost in Customer Churn Prediction
8 references·3 citing·42 second hop
The Application ofAdaBoost in Customer Churn Prediction (2007)The Application ofAdaBoost in Customer Ch…Bagging and Boosting Classification Trees to Predict Churn (2006)Bagging and Boosting Classifi…Customer Churn Prediction Using Improved One-Class Support Vector Machine (2005)Customer Churn Prediction Usi…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…Data Mining and Causal Modeling of Customer Behaviors (2002)Data Mining and Causal Modeli…Churn Reduction in the Wireless Industry (1999)Churn Reduction in the Wirele…Genetic modelling of customer retention (1998)Genetic modelling of customer…Game theory, on-line prediction and boosting (1996)Game theory, on-line predicti…A High-Performance Customer Churn Prediction System Based on Self-Attention (2022)A High-Performance Customer C…Prediction of Advertiser Churn for Google AdWords (2010)Prediction of Advertiser Chur…Ensembles of Probability Estimation Trees for Customer Churn Prediction (2010)Ensembles of Probability Esti…Improved statistical techniques for response modeling (1988)LEARNING FROM CUSTOMER DEFECTIONS (1996)Direct marketing modeling with CART and CHAID (1997)A Personalized Defection Detection and Prevention Procedure based on the Self-Organizing Map and Association Rule Mining: Applied to Online Game Site (2004)Churn prediction with Linear Discriminant Boosting algorithm (2008)Customer churn prediction for retail business (2017)Latent Variable Modeling and Applications to Causality (1997)Support vector machine for regression and applications to financial forecasting (2000)Defection Detection: Measuring and Understanding the Predictive Accuracy of Customer Churn Models (2006)Domain knowledge integration in data mining using decision tables: case studies in churn prediction (2009)An extended support vector machine forecasting framework for customer churn in e-commerce (2010)Propension to customer churn in a financial institution: a machine learning approach (2022)A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)Knowledge management and data mining for marketing (2001)The mismanagement of customer loyalty. (2002)Evalu ations of Data Mining Methods in Order to Provide the Optimum Method for Customer Churn Prediction: Case Study Insurance Industry (2012)A SLR on Customer Dropout Prediction (2022)A Logit Model of Brand Choice Calibrated on Scanner Data (1983)Market Segmentation: Conceptual and Methodological Foundations (1997)Understanding the Customer Base of Service Providers: An Examination of the Differences between Switchers and Stayers (2000)Customer churn prediction using improved balanced random forests (2008)Gradient boosting trees for auto insurance loss cost modeling and prediction (2011)Retention Futility: Targeting High-Risk Customers Might be Ineffective (2017)Building Data Mining Applications for CRM (1999)New insights into churn prediction in the telecommunication sector: A profit driven data mining approach (2011)A comparison of machine learning techniques for customer churn prediction (2015)Customer churn prediction in telecom using machine learning in big data platform (2019)An analog of the minimax theorem for vector payoffs (1956)Regret in the On-Line Decision Problem (1999)Competitive On‐line Statistics (2001)Online Learning: Theory, Algorithms, and Applications (2007)Predicting subscriber dissatisfaction and improving retention in the wireless telecommunications industry (2000)Computer assisted customer churn management: State-of-the-art and future trends (2005)Social ties and their relevance to churn in mobile telecom networks (2008)Customer churn prediction in telecommunications (2011)Explaining Rare Events in International Relations (2001)Applying data mining to telecom churn management (2005)Churn prediction in subscription services: An application of support vector machines while comparing two parameter-selection techniques (2006)Performing Highly Accurate Predictions Through Convolutional Networks for Actual Telecommunication Challenges (2015)Modelling and evaluating service quality measurement using neural networks (2002)Performance modeling of Indian business schools: a DEA‐neural network approach (2011)Applying over 100 classifiers for churn prediction in telecom companies (2020)
this work references cited by second hop

References

  • 2002Turning telecommunications call details to churn prediction: a data mining approach460 cited
  • 2006Bagging and Boosting Classification Trees to Predict Churn410 cited
  • 1996Game theory, on-line prediction and boosting383 cited
  • 2003A novel evolutionary data mining algorithm with applications to churn prediction348 cited
  • 2005Customer Churn Prediction Using Improved One-Class Support Vector Machine102 cited
  • 1999Churn Reduction in the Wireless Industry47 cited
  • 1998Genetic modelling of customer retention29 cited
  • 2002Data Mining and Causal Modeling of Customer Behaviors19 cited

Cited by

  • 2010Prediction of Advertiser Churn for Google AdWords16 cited
  • 2010Ensembles of Probability Estimation Trees for Customer Churn Prediction12 cited
  • 2022A High-Performance Customer Churn Prediction System Based on Self-Attention10 cited

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