Using Human Resources (HR) Data to Predict Staff Turnover in a Community Mental Health Center (CMHC): A Comparison of Two Machine Learning (ML) Approaches

The current study used machine learning with random forest (RF) and logistic regression (LG) to predict turnover in a Midwest mental health center from their historical HR data. The result suggests that HR data could provide a decent prediction of turnover, and RF outperformed LG in overall prediction accuracy.