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Analysis of imbalanced data set problem: The case of churn prediction for telecommunication
4 references·3 citing·32 second hop
Analysis of imbalanced data set problem: The case of churn prediction for telecommunication (2017)Analysis of imbalanced data set problem: …Improved churn prediction in telecommunication industry using data mining techniques (2014)Improved churn prediction in …Churn prediction in telecom using Random Forest and PSO based data balancing in combination with various feature selection strategies (2012)Churn prediction in telecom u…Applying Bayesian Belief Network approach to customer churn analysis: A case study on the telecom industry of Turkey (2010)Applying Bayesian Belief Netw…Applying data mining to telecom churn management (2005)Applying data mining to telec…Müşteri Kaybı Tahmininde Sınıf Dengesizliği Problemi (2020)Müşteri Kaybı Tahmininde Sını…Telecommunication Services Churn Prediction - Deep Learning Approach (2018)Telecommunication Services Ch…Customer Churn Analysis for Telecom Operators Based on SVM (2017)Customer Churn Analysis for T…Experiments in induction (1966)Experiments in Induction (1967)A Data Mining-Based Framework for Supply Chain Risk Management (2018)Machine-Learning Techniques for Customer Retention: A Comparative Study (2018)Predicting Employee Attrition Using Machine Learning Techniques (2020)Turning telecommunications call details to churn prediction: a data mining approach (2002)Determinants of subscriber churn and customer loyalty in the Korean mobile telephony market (2004)Predicting customer churn from valuable B2B customers in the logistics industry: a case study (2014)Assessment of lean manufacturing effect on business performance using Bayesian Belief Networks (2015)Intelligent data analysis approaches to churn as a business problem: a survey (2016)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)Customer churn prediction using improved balanced random forests (2008)Early churn prediction with personalized targeting in mobile social games (2017)A Survey on Churn Analysis in Various Business Domains (2020)Carbon price forecasting based on modified ensemble empirical mode decomposition and long short-term memory optimized by improved whale optimization algorithm (2020)Managerial Applications of Neural Networks: The Case of Bank Failure Predictions (1992)Artificial neural networks in bankruptcy prediction: General framework and cross-validation analysis (1999)Building Data Mining Applications for CRM (1999)New insights into churn prediction in the telecommunication sector: A profit driven data mining approach (2011)A survey of results on mobile phone datasets analysis (2015)A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees (2018)Model of Customer Churn Prediction on Support Vector Machine (2008)Customer churn prediction by hybrid neural networks (2009)A Multi-Layer Perceptron Approach for Customer Churn Prediction (2015)Churn analysis using deep convolutional neural networks and autoencoders (2016)Designing of customer and employee churn prediction model based on data mining method and neural predictor (2017)Analysis of customer churn prediction using machine learning and deep learning algorithms (2022)Deep Convolutional Neural Network Based Churn Prediction for Telecommunication Industry (2022)Machine Learning and Deep Learning technique used in Customer Churn Prediction: - A Review (2023)A comparison of machine learning techniques for customer churn prediction (2015)A Churn Prediction Model Using Random Forest: Analysis of Machine Learning Techniques for Churn Prediction and Factor Identification in Telecom Sector (2019)
this work references cited by second hop

References

  • 2005Applying data mining to telecom churn management514 cited
  • 2014Improved churn prediction in telecommunication industry using data mining techniques176 cited
  • 2012Churn prediction in telecom using Random Forest and PSO based data balancing in combination with various feature selection strategies138 cited
  • 2010Applying Bayesian Belief Network approach to customer churn analysis: A case study on the telecom industry of Turkey124 cited

Cited by

  • 2018Telecommunication Services Churn Prediction - Deep Learning Approach22 cited
  • 2017Customer Churn Analysis for Telecom Operators Based on SVM11 cited
  • 2020Müşteri Kaybı Tahmininde Sınıf Dengesizliği Problemi8 cited

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