EMPLOYEE PERFORMANCE AND ATTRITION PREDICTION USING MACHINE LEARNING AND GENERATIVE AI

Employee attrition is a major challenge for organizations, leading to productivity loss, higher recruitment costs, and disruption in operations. This paper presents an Employee Performance and Attrition Prediction System that combines HR management with machine learning and generative AI. The system is built using Django with SQLite as the database and uses Python libraries such as Scikit-learn for prediction, Openpyxl for data export, and Google Gemini API for generating explanations. It stores structured employee data including performance, attendance, and evaluations for analysis. A classification model predicts attrition risk based on factors like performance rating, projects completed, and salary. To improve interpretability, a generative AI module explains predictions in simple HR-friendly language.Overall, the system improves data management, enhances prediction accuracy, and provides an easy-to-understand, scalable solution for workforce analysis and decision-making.