Predictive Retention Tools: Bridging Data and Action

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This project explores the development of a Machine Learning-Explainable AI (ML-XAI) tool aimed at addressing the decline of union membership in the private sector by enhancing engagement through predictive analytics. The research focuses on designing a defensible retention model, utilising techniques like XGBoost and SHAP within Power BI. Despite being centred on a single organisation, the study provides insights into churn prediction and explainability, fostering trust and informed decision-...