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pRNN: A Recurrent Neural Network based Approach for Customer Churn Prediction in Telecommunication Sector
6 references·2 citing·39 second hop
pRNN: A Recurrent Neural Network based Approach for Customer Churn Prediction in Telecommunication Sector (2018)pRNN: A Recurrent Neural Network based Ap…Deep Learning in Customer Churn Prediction: Unsupervised Feature Learning on Abstract Company Independent Feature Vectors (2017)Deep Learning in Customer Chu…Hidden Markov models for churn prediction (2015)Hidden Markov models for chur…Predicting partial customer churn using Markov for discrimination for modeling first purchase sequences (2012)Predicting partial customer c…A Novel Profit Maximizing Metric for Measuring Classification Performance of Customer Churn Prediction Models (2012)A Novel Profit Maximizing Met…Customer churn prediction using improved balanced random forests (2008)Customer churn prediction usi…Churn prediction in subscription services: An application of support vector machines while comparing two parameter-selection techniques (2006)Churn prediction in subscript…Lifelog Data-Based Prediction Model of Digital Health Care App Customer Churn: Retrospective Observational Study (2020)Lifelog Data-Based Prediction…Deep Learning Based Customer Churn Analysis (2019)Deep Learning Based Customer …A Logit Model of Brand Choice Calibrated on Scanner Data (1983)Customer Evaluations of Service Complaint Experiences: Implications for Relationship Marketing (1998)Switching barriers and repurchase intentions in services (2000)Building comprehensible customer churn prediction models with advanced rule induction techniques (2010)Customer churn prediction in telecommunications (2011)Customer Loyalty: Toward an Integrated Conceptual Framework (1994)The Behavioral Consequences of Service Quality (1996)Marketing management: analysis. planning. implementation and control (2000)A Genetic Programming Based Framework for Churn Prediction in Telecommunication Industry (2014)Predicting customer churn for platform businesses: using latent variables of variational autoencoder as consumers’ purchasing behavior (2022)A comprehensive survey on customer churn analysis studies (2025)Customer base analysis: partial defection of behaviourally loyal clients in a non-contractual FMCG retail setting (2004)Defection Detection: Measuring and Understanding the Predictive Accuracy of Customer Churn Models (2006)A comparative analysis of data preparation algorithms for customer churn prediction: A case study in the telecommunication industry (2016)A machine learning framework for customer purchase prediction in the non-contractual setting (2018)Customer churn prediction system: a machine learning approach (2021)Introduction to Data Mining (2007)New insights into churn prediction in the telecommunication sector: A profit driven data mining approach (2011)Development and application of consumer credit scoring models using profit-based classification measures (2014)Improved churn prediction in telecommunication industry using data mining techniques (2014)Two-stage consumer credit risk modelling using heterogeneous ensemble learning (2019)Zero defections: quality comes to services. (1990)Intelligence Generation and Superior Customer Value (2000)The Impact of Customer Relationship Characteristics on Profitable Lifetime Duration (2003)Combining Sequential and Aggregated Data for Churn Prediction in Casual Freemium Games (2019)Measuring Player Retention and Monetization Using the Mean Cumulative Function (2020)Determinants of subscriber churn and customer loyalty in the Korean mobile telephony market (2004)Handling class imbalance in customer churn prediction (2008)A Blended Deep Learning Approach for Predicting User Intended Actions (2018)An inclusive survey on machine learning for CRM: a paradigm shift (2020)Deep Learning and Implementations in Banking (2020)Analysis of customer churn prediction in telecom industry using decision trees and logistic regression (2016)A deep learning framework for financial time series using stacked autoencoders and long-short term memory (2017)A Novel Approach for Churn Prediction Using Deep Learning (2017)Analysis of customer churn prediction using machine learning and deep learning algorithms (2022)Sampling-based novel heterogeneous multi-layer stacking ensemble method for telecom customer churn prediction (2024)Who succeeds in maintaining weight loss? A conceptual review of factors associated with weight loss maintenance and weight regain (2005)Beyond the hype: Big data concepts, methods, and analytics (2014)Predicting early user churn in a public digital weight loss intervention (2024)
this work references cited by second hop

References

  • 2006Churn prediction in subscription services: An application of support vector machines while comparing two parameter-selection techniques432 cited
  • 2008Customer churn prediction using improved balanced random forests412 cited
  • 2012A Novel Profit Maximizing Metric for Measuring Classification Performance of Customer Churn Prediction Models177 cited
  • 2017Deep Learning in Customer Churn Prediction: Unsupervised Feature Learning on Abstract Company Independent Feature Vectors36 cited
  • 2015Hidden Markov models for churn prediction28 cited
  • 2012Predicting partial customer churn using Markov for discrimination for modeling first purchase sequences25 cited

Cited by

  • 2020Lifelog Data-Based Prediction Model of Digital Health Care App Customer Churn: Retrospective Observational Study20 cited
  • 2019Deep Learning Based Customer Churn Analysis17 cited

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