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A Two-Stage Ensemble Approach for Analysis of Optimizing Customer Churn with Lime Interpretability
12 references·0 citing·43 second hop
A Two-Stage Ensemble Approach for Analysis of Optimizing Customer Churn with Lime Interpretability (2024)A Two-Stage Ensemble Approach for Analysi…Predicting customer churn using grey wolf optimization‐based support vector machine with principal component analysis (2023)Predicting customer churn usi…Hyperparameter Optimization and Combined Data Sampling Techniques in Machine Learning for Customer Churn Prediction: A Comparative Analysis (2023)Hyperparameter Optimization a…Extreme gradient boosting trees with efficient Bayesian optimization for profit-driven customer churn prediction (2023)Extreme gradient boosting tre…Ensemble Methods in Customer Churn Prediction: A Comparative Analysis of the State-of-the-Art (2023)Ensemble Methods in Customer …Analyzing Employee Attrition Using Explainable AI for Strategic HR Decision-Making (2023)Analyzing Employee Attrition …Analysis Implementation of the Ensemble Algorithm in Predicting Customer Churn in Telco Data: A Comparative Study (2023)Analysis Implementation of th…A Data-Driven Decision Support Framework for Player Churn Analysis in Online Games (2023)A Data-Driven Decision Suppor…Research on telecom customer churn prediction based on ensemble learning (2022)Research on telecom customer …Predicting customers churning in banking industry: A machine learning approach (2022)Predicting customers churning…Analysis of Telecom Churn using Machine Learning Techniques (2022)Analysis of Telecom Churn usi…Predictive Analysis and Modeling of Customer Churn in Telecom using Machine Learning Technique (2019)Predictive Analysis and Model…A data-driven approach to predict the success of bank telemarketing (2014)A data-driven approach to pre…A framework for marketing management (2000)Decision Support and Business Intelligence Systems (2006)AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias (2019)A Review on Fairness in Machine Learning (2022)The effects of data quality on machine learning performance on tabular data (2025)Customer churn prediction using improved balanced random forests (2008)Credit card churn forecasting by logistic regression and decision tree (2011)Customer churn prediction in telecom using machine learning in big data platform (2019)Customer Churn Prevention For E-commerce Platforms using Machine Learning-based Business Intelligence (2023)Interpretable Machine Learning for Predicting Customer Churn in Retail Banking (2023)Applying data mining to telecom churn management (2005)A Churn Prediction Model Using Random Forest: Analysis of Machine Learning Techniques for Churn Prediction and Factor Identification in Telecom Sector (2019)TSUNAMI - an explainable PPM approach for customer churn prediction in evolving retail data environments (2023)A Model-Agnostic Interpretability Approach to Predicting Customer Churn in the Telecommunications Industry (2024)Optimising customer retention: An AI-driven personalised pricing approach (2024)Understanding the Customer Base of Service Providers: An Examination of the Differences between Switchers and Stayers (2000)A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees (2018)Hyperparameter tuning and performance assessment of statistical and machine-learning algorithms using spatial data (2019)Deep Dive Into Churn Prediction in the Banking Sector: The Challenge of Hyperparameter Selection and Imbalanced Learning (2024)Multi-Layer Perceptron and Radial Basis Function Networks in Predictive Modeling of Churn for Mobile Telecommunications Based on Usage Patterns (2024)Benchmarking state-of-the-art classification algorithms for credit scoring (2003)Defection Detection: Measuring and Understanding the Predictive Accuracy of Customer Churn Models (2006)Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research (2015)A Mathematical Model for Customer Segmentation Leveraging Deep Learning, Explainable AI, and RFM Analysis in Targeted Marketing (2023)Customer Churn Prediction for Telecommunication Companies using Machine Learning and Ensemble Methods (2024)Mitigating class imbalance in churn prediction with ensemble methods and SMOTE (2025)Turning telecommunications call details to churn prediction: a data mining approach (2002)Customer churn analysis in telecom industry (2015)A Survey on Customer Churn Prediction using Machine Learning Techniques (2016)Business Intelligence and Analytics: From Big Data to Big Impact (2012)The mismanagement of customer loyalty. (2002)A novel classification algorithm for customer churn prediction based on hybrid Ensemble-Fusion model (2024)Profit-driven fusion framework based on bagging and boosting classifiers for potential purchaser prediction (2024)Profit-driven weighted classifier with interpretable ability for customer churn prediction (2024)Stacked Regressions (1996)Data preprocessing techniques for classification without discrimination (2011)Predicting Employee Attrition Using Machine Learning Techniques (2020)From Recruitment to Retention: AI Tools for Human Resource Decision-Making (2024)A Deep Learning Model Based on Bidirectional Temporal Convolutional Network (Bi-TCN) for Predicting Employee Attrition (2025)Predicting Employee Attrition: XAI-Powered Models for Managerial Decision-Making (2025)Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management (2004)The Impact of SMOTE and ADASYN on Random Forest and Advanced Gradient Boosting Techniques in Telecom Customer Churn Prediction (2024)Customer Churn Prediction: A Systematic Review of Recent Advances, Trends, and Challenges in Machine Learning and Deep Learning (2025)
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References

  • 2014A data-driven approach to predict the success of bank telemarketing875 cited
  • 2023Analyzing Employee Attrition Using Explainable AI for Strategic HR Decision-Making89 cited
  • 2023Extreme gradient boosting trees with efficient Bayesian optimization for profit-driven customer churn prediction79 cited
  • 2023Hyperparameter Optimization and Combined Data Sampling Techniques in Machine Learning for Customer Churn Prediction: A Comparative Analysis71 cited
  • 2023Ensemble Methods in Customer Churn Prediction: A Comparative Analysis of the State-of-the-Art59 cited
  • 2022Predicting customers churning in banking industry: A machine learning approach38 cited
  • 2022Research on telecom customer churn prediction based on ensemble learning29 cited
  • 2023Predicting customer churn using grey wolf optimization‐based support vector machine with principal component analysis22 cited
  • 2023Analysis Implementation of the Ensemble Algorithm in Predicting Customer Churn in Telco Data: A Comparative Study19 cited
  • 2022Analysis of Telecom Churn using Machine Learning Techniques17 cited
  • 2019Predictive Analysis and Modeling of Customer Churn in Telecom using Machine Learning Technique17 cited
  • 2023A Data-Driven Decision Support Framework for Player Churn Analysis in Online Games13 cited

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