Customer Churn Prediction to Enhance Customer Retention Strategies in the Banking Industry: A Study Using Seven Machine Learning Algorithms
Journal of Software and Systems Development
This study explores machine learning approaches to predict customer churn in the banking sector. Following Dietterich’s Machine Learning Problem Research Life Cycle, six key steps were implemented: data gathering, preparation, exploratory data analysis (EDA), model creation, training, evaluation, and hyperparameter tuning. A systematic literature review…
