AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
TL;DR
These findings demonstrate that combining heterogeneous algorithms yields a reliable boost in predictive accuracy for both churn and potential return, informing more cost-effective retention and win-back strategies.
The Extreme Gradient Boosting algorithm is applied to telecom customer churn prediction, comparing its performance with Logistic Regression and Random Forest using the public Telco Customer Churn dataset and showing XGBoost outperformed benchmark models.
Customer churn remains one of the most consequential problems facing business enterprises globally. Compared with the enticement and acquisition costs associated with acquiring new customers, retaining an existing subscriber is substantially cheaper. Due to its significance to business sustainability, various studies h...
This study proposes the Adaptive Multidimensional Rebalancing (AMR) framework, a framework that dynamically evaluates the local topological structure of the feature space, specifically local density, class overlap, and feature variability, to adap-tively allocate synthetic minority samples.
Customer churn prediction is an important task in the telecommunications sector, particularly when class imbalance affects the ability of machine learning models to identify churned customers. This study evaluates the performance of several machine learning algorithms using the Telco Customer Churn dataset, which conta...
. Customer churn prediction has a great impact on the long-term profitability and competitiveness of telecommunications companies. This study uses telecommunications customer data, employs machine learning methods to build a customer churn prediction model, and identifies key influencing factors. By using majority clas...
This study demonstrates that PLSDA-optimized machine learning achieves competitive accuracy with reduced computational complexity and enhanced interpretability in churn prediction, while meeting regulatory compliance requirements for practical banking implementations.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.