Citation map · Study

SZodixStudyAcademic Library

Shelves Open access

Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated

A comparative study of customer churn prediction in telecom industry using ensemble based classifiers

3 references·15 citing·34 second hop

FromToDepth

this work references cited by second hop

References

2003A novel evolutionary data mining algorithm with applications to churn prediction348 cited
2000Predicting subscriber dissatisfaction and improving retention in the wireless telecommunications industry347 cited
2012A Customer Churn Prediction Model in Telecom Industry Using Boosting185 cited

Cited by

2024Enhancing customer retention in telecom industry with machine learning driven churn prediction69 cited
2024ChurnNet: Deep Learning Enhanced Customer Churn Prediction in Telecommunication Industry65 cited
2022An ensemble based approach using a combination of clustering and classification algorithms to enhance customer churn prediction in telecom industry45 cited
2019Customer Churn Prediction In Telecommunication Industry Using Machine Learning Classifiers40 cited
2024Customer churn prediction model based on hybrid neural networks37 cited
2022Intelligent Decision Forest Models for Customer Churn Prediction32 cited
2021CUSTOMER CHURN PREDICTION29 cited
2020Machine Learning Based Telecom-Customer Churn Prediction24 cited
2023Prediction of customer churn using resampling and ensemble classification algorithms on telecom dataset19 cited
2024Hybrid Machine Learning Models for Predictive Maintenance in Cloud-Based Infrastructure for SaaS Applications19 cited
2020

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

Churning of Bank Customers Using Supervised Learning

18 cited

2024A comprehensive framework for customer retention in E-commerce using machine learning based on churn prediction, customer segmentation, and recommendation17 cited

2024Sampling-based novel heterogeneous multi-layer stacking ensemble method for telecom customer churn prediction12 cited

2021A Novel Model Structured on Predictive Churn Methods in a Banking Organization10 cited

2024Assessing the effectiveness of OTT services, branded apps, and gamified loyalty giveaways on mobile customer churn in the telecom industry: A machine-learning approach9 cited