Blerina Çeliku

Predictive Analytics for Customer Retention: Designing and Evaluating a Machine Learning–Based Churn Prediction System

Results demonstrate that ensemble models, particularly those trained using the Random Forest and Gradient Boosting algorithms, outperform baseline approaches across all selected evaluation metrics, and these algorithms are recommended for identifying potential churners across various business and industrial use cases.