An Improved Ant Colony Optimization to Uncover Customer Characteristics for Churn Prediction

An Improved Ant Colony Optimization to Uncover Customer Characteristics for Churn Prediction

Customer churn prediction is a critical task in the telecommunication (telecom) industry, where accurate identification of customers at risk of churning plays a vital role in reducing customer attrition. Feature selection (FS) is an integral part in Machine Learning (ML) models which aims to improve...

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Bibliographic Details
Main Authors: Ibrahim Al-Shourbaji, Abdoh Jabbari, Shaik Rizwan, Mostafa Mehanawi, Phiros Mansur, Mohammed Abdalraheem
Format: Article
Language:English
Published: The Scientific Association for Studies and Applied Research 2025-04-01
Series:Computational Journal of Mathematical and Statistical Sciences
Subjects:
ant colony optimization
churn prediction
feature selection
Online Access:https://cjmss.journals.ekb.eg/article_385616.html
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