This decision tree model was built using BigML to predict employee attrition based on various HR attributes such as OverTime, Age, JobSatisfaction, BusinessTravel, and TotalWorkingYears. The target variable is Attrition (Yes/No). The model analyzes patterns in historical data to classify employees as likely to stay or leave. It helps identify high-risk employee profiles and provides insights for HR decision-making.

This predictive model was trained on 80% of the HR Analytics dataset to classify whether an employee is likely to leave the organization (Attrition = Yes/No). Using a decision tree algorithm in BigML, the model learned patterns from features such as OverTime, BusinessTravel, TotalWorkingYears, Age, and JobSatisfaction. It serves as the foundation for evaluation and simulation, enabling HR teams to identify key risk factors and develop retention strategies.