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Bank Customer Churn Prediction Based on Support Vector Machine: Taking a Commercial Bank's VIP Customer Churn as the Example
4 references·7 citing·45 second hop
Bank Customer Churn Prediction Based on Support Vector Machine: Taking a Commercial Bank's VIP Customer Churn as the Example (2008)Bank Customer Churn Prediction Based on S…Customer Perception, Customer Satisfaction, and Customer Loyalty Within Chinese Securities Business (2007)Customer Perception, Customer…Determinants of subscriber churn and customer loyalty in the Korean mobile telephony market (2004)Determinants of subscriber ch…Predicting subscriber dissatisfaction and improving retention in the wireless telecommunications industry (2000)Predicting subscriber dissati…Why Satisfied Customers Defect (1996)Why Satisfied Customers DefectImproving bank customer churn prediction with feature reduction using GA (2025)Improving bank customer churn…Churning of Bank Customers Using Supervised Learning (2020)Churning of Bank Customers Us…Churn Prediction for Savings Bank Customers: A Machine Learning Approach (2020)Churn Prediction for Savings …Towards Accurate Predictions of Customer Purchasing Patterns (2017)Towards Accurate Predictions …Churn Prediction in Customer Relationship Management via GMDH-Based Multiple Classifiers Ensemble (2016)Churn Prediction in Customer …Data Mining Applications in Customer Churn Management (2010)Data Mining Applications in C…An experimental study on four models of customer churn prediction (2009)An experimental study on four…Structural equation modeling in practice: A review and recommended two-step approach. (1988)Alternative Ways of Assessing Model Fit (1992)The Commitment-Trust Theory of Relationship Marketing (1994)Dimensions of Relationship Marketing in Business-to-Business Financial Services (2010)Towards an integrated model of customer service skills and customer loyalty (2011)The influence of service quality on customer satisfaction and customer behavioral intentions by moderating role of switching barriers in satellite pay TV market (2018)The effects of customer satisfaction and switching barrier on customer loyalty in Korean mobile telecommunication services (2004)Decision Support and Business Intelligence Systems (2006)Application of data mining techniques in customer relationship management: A literature review and classification (2008)The Architecture of a Churn Prediction System Based on Stream Mining (2013)IG-KNN UNTUK PREDIKSI CUSTOMER CHURN TELEKOMUNIKASI (2015)Customer churn analysis using XGBoosted decision trees (2022)Next-product-to-buy models for cross-selling applications (2002)Applying data mining to telecom churn management (2005)Customer Churn Prediction Based on the Decision Tree in Personal Handyphone System Service (2007)SERVQUAL: A multiple-Item Scale for measuring consumer perceptions of service quality (1988)Customer Loyalty: Toward an Integrated Conceptual Framework (1994)The relationships of customer satisfaction, customer loyalty, and profitability: an empirical study (1996)M‐loyalty: winning strategies for mobile carriers (2006)Determinants of customer loyalty in the wireless telecommunications industry (2007)Improved churn prediction in telecommunication industry using data mining techniques (2014)Bagging and Boosting Classification Trees to Predict Churn (2006)Customer churn prediction using improved balanced random forests (2008)Predicting customer churn in mobile networks through analysis of social groups (2010)K- local maximum margin feature extraction algorithm for churn prediction in telecom (2017)Churn prediction and social neighbour influences for different types of user groups in virtual worlds (2019)Hybrid ensemble learning approaches to customer churn prediction (2021)Accelerating Customer Relationships: Using Crm and Relationship Technologies (2000)The comparisons of data mining techniques for the predictive accuracy of probability of default of credit card clients (2008)Customer churn prediction in the telecommunication sector using a rough set approach (2016)Customer churn prediction in telecom using machine learning in big data platform (2019)Predicting Banking Customer Churn based on Artificial Neural Network (2022)An Efficient Customer Churn Prediction Technique Using Combined Machine Learning in Commercial Banks (2024)Multi-Level Machine Learning Model to Improve the Effectiveness of Predicting Customers Churn Banks (2024)Measurement of Inequality of Incomes (1921)Handling class imbalance in customer churn prediction (2008)Marketing metrics: the definitive guide to measuring marketing performance (2010)Enhancing Customer Churn Prediction in Digital Banking using Ensemble Modeling (2022)Optimized churn prediction using ensemble-based feature selection via second-order cone programming (2025)Examining the structural relationships of destination image, tourist satisfaction and destination loyalty: An integrated approach (2007)How quality, value, image, and satisfaction create loyalty at a Chinese telecom (2008)Modelling perceived quality, visitor satisfaction and behavioural intentions at the destination level (2009)A novel evolutionary data mining algorithm with applications to churn prediction (2003)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)
this work references cited by second hop

References

  • 1996Why Satisfied Customers Defect809 cited
  • 2004Determinants of subscriber churn and customer loyalty in the Korean mobile telephony market417 cited
  • 2000Predicting subscriber dissatisfaction and improving retention in the wireless telecommunications industry347 cited
  • 2007Customer Perception, Customer Satisfaction, and Customer Loyalty Within Chinese Securities Business86 cited

Cited by

  • 2016Churn Prediction in Customer Relationship Management via GMDH-Based Multiple Classifiers Ensemble30 cited
  • 2020Churn Prediction for Savings Bank Customers: A Machine Learning Approach20 cited
  • 2010Data Mining Applications in Customer Churn Management19 cited
  • 2020Churning of Bank Customers Using Supervised Learning18 cited
  • 2017Towards Accurate Predictions of Customer Purchasing Patterns12 cited
  • 2009An experimental study on four models of customer churn prediction11 cited
  • 2025Improving bank customer churn prediction with feature reduction using GA9 cited

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