Customer churn prediction in telecom using machine learning - Faraz, Ahmed; Ullah Bazai, Sibghat; Hussain, Shumaila; Shahwani, Hamayoun Yousaf; Baryalai, Mehmood; Fakhar, Shariqa (Journal of Advanced Computer Science & Technology, 2024)
The customer churn prediction has become crucial for retaining customers in rapidly growing telecommunication industry. It enables telecommunication industry to avoid sizeable revenue losses. There are many techniques available to analyze the customer churn. It is still a challenging task due to large data size, imbalanced class distribution, and high dimensionality of telecom datasets.This study contributes to formalize customer churn prediction. The study investigates the most promising machine learning algorithms XGboost and Logistic Regression. Furthermore; the feature extraction will be used before implementing the classification algorithms in order to analyze the impact.