SZodixStudyAcademic Library
ShelvesOpen access
Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated
A Review of Machine Learning Methods For Predicting Churn in the Telecom Sector
16 references·0 citing·40 second hop
A Review of Machine Learning Methods For Predicting Churn in the Telecom Sector (2023)A Review of Machine Learning Methods For …Model Optimization Analysis of Customer Churn Prediction Using Machine Learning Algorithms with Focus on Feature Reductions (2022)Model Optimization Analysis o…Blockchain in churn prediction based telecommunication system on climatic weather application (2022)Blockchain in churn predictio…Machine Learning: Algorithms, Real-World Applications and Research Directions (2021)Machine Learning: Algorithms,…Deep Learning as a Vector Embedding Model for Customer Churn (2021)Deep Learning as a Vector Emb…A Prediction Model of Customer Churn considering Customer Value: An Empirical Research of Telecom Industry in China (2021)A Prediction Model of Custome…Dynamic behavior based churn prediction in mobile telecom (2020)Dynamic behavior based churn …Customer switching behavior analysis in the telecommunication industry via push-pull-mooring framework: A machine learning approach (2020)Customer switching behavior a…Churn Prediction in Telecommunication using Logistic Regression and Logit Boost (2020)Churn Prediction in Telecommu…Customer churn prediction in telecom using machine learning in big data platform (2019)Customer churn prediction in …Customer churn prediction in telecommunication industry using data certainty (2018)Customer churn prediction in …Cross-company customer churn prediction in telecommunication: A comparison of data transformation methods (2018)Cross-company customer churn …A REVIEW ON CUSTOMER CHURN PREDICTION DATA MINING MODELING TECHNIQUES (2018)A REVIEW ON CUSTOMER CHURN PR…An empirical comparison of techniques for the class imbalance problem in churn prediction (2017)An empirical comparison of te…A comparative analysis of data preparation algorithms for customer churn prediction: A case study in the telecommunication industry (2016)A comparative analysis of dat…An effective hybrid learning system for telecommunication churn prediction (2013)An effective hybrid learning …Churn analysis for an Iranian mobile operator (2011)Churn analysis for an Iranian…Customer retention, loyalty, and satisfaction in the German mobile cellular telecommunications market (2001)Issues in Linking Information Technology Capability to Firm Performance1 (2003)The effects of customer satisfaction and switching barrier on customer loyalty in Korean mobile telecommunication services (2004)How value and trust influence loyalty in wireless telecommunications industry (2012)An integrative framework for customer switching behavior (2018)Data preparation for data mining (1999)Understanding the Customer Base of Service Providers: An Examination of the Differences between Switchers and Stayers (2000)Credit Scoring and Its Applications (2002)A Review on Machine Learning Methods for Customer Churn Prediction and Recommendations for Business Practitioners (2024)Defection Detection: Measuring and Understanding the Predictive Accuracy of Customer Churn Models (2006)Handling class imbalance in customer churn prediction (2008)A Churn Prediction Model Using Random Forest: Analysis of Machine Learning Techniques for Churn Prediction and Factor Identification in Telecom Sector (2019)Explaining and predicting employees’ attrition: a machine learning approach (2020)Customer Satisfaction Cues To Support Market Segmentation and Explain Switching Behavior (2000)LightGBM: an Effective Decision Tree Gradient Boosting Method to Predict Customer Loyalty in the Finance Industry (2019)Data Cleaning: Problems and Current Approaches. (2000)Understanding customer satisfaction and loyalty: An empirical study of mobile instant messages in China (2009)An Empirical Study on Customer Segmentation by Purchase Behaviors Using a RFM Model and K-Means Algorithm (2020)From user-generated data to data-driven innovation: A research agenda to understand user privacy in digital markets (2021)Turning telecommunications call details to churn prediction: a data mining approach (2002)Customer churn prediction system: a machine learning approach (2021)Customer Churn Prediction in Telecom Sector Using Machine Learning Techniques (2022)A novel evolutionary data mining algorithm with applications to churn prediction (2003)Customer churn prediction in the telecommunication sector using a rough set approach (2016)A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees (2018)B2C E-Commerce Customer Churn Prediction Based on K-Means and SVM (2022)Deep Churn Prediction Method for Telecommunication Industry (2023)Zero defections: quality comes to services. (1990)An Introduction to Copulas (1999)Dependence Modeling with Copulas (2014)A machine learning-based iterative design approach to automate user satisfaction degree prediction in smart product-service system (2022)Consumer switching behavior to an augmented reality (AR) beauty product application: Push-pull mooring theory framework (2023)Investigating customer churn in banking: a machine learning approach and visualization app for data science and management (2023)Applying data mining to telecom churn management (2005)A comparison of machine learning techniques for customer churn prediction (2015)A Swish RNN based customer churn prediction for the telecom industry with a novel feature selection strategy (2022)Customer Churn Prediction: A Systematic Review of Recent Advances, Trends, and Challenges in Machine Learning and Deep Learning (2025)Data Science and Analytics: An Overview from Data-Driven Smart Computing, Decision-Making and Applications Perspective (2021)Future smart cities: requirements, emerging technologies, applications, challenges, and future aspects (2022)Smart City Data Science: Towards data-driven smart cities with open research issues (2022)
this work references cited by second hop

References

  • 2021Machine Learning: Algorithms, Real-World Applications and Research Directions5,577 cited
  • 2019Customer churn prediction in telecom using machine learning in big data platform576 cited
  • 2018Customer churn prediction in telecommunication industry using data certainty251 cited
  • 2016A comparative analysis of data preparation algorithms for customer churn prediction: A case study in the telecommunication industry214 cited
  • 2017An empirical comparison of techniques for the class imbalance problem in churn prediction161 cited
  • 2020Churn Prediction in Telecommunication using Logistic Regression and Logit Boost160 cited
  • 2020Dynamic behavior based churn prediction in mobile telecom114 cited
  • 2018Cross-company customer churn prediction in telecommunication: A comparison of data transformation methods102 cited
  • 2011Churn analysis for an Iranian mobile operator95 cited
  • 2020Customer switching behavior analysis in the telecommunication industry via push-pull-mooring framework: A machine learning approach94 cited
  • 2013An effective hybrid learning system for telecommunication churn prediction90 cited
  • 2022Model Optimization Analysis of Customer Churn Prediction Using Machine Learning Algorithms with Focus on Feature Reductions44 cited
  • 2021A Prediction Model of Customer Churn considering Customer Value: An Empirical Research of Telecom Industry in China41 cited

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

  • 2021Deep Learning as a Vector Embedding Model for Customer Churn37 cited
  • 2018A REVIEW ON CUSTOMER CHURN PREDICTION DATA MINING MODELING TECHNIQUES17 cited
  • 2022Blockchain in churn prediction based telecommunication system on climatic weather application15 cited
  • Cited by

    No citing works inside the corpus for this window.