Predicting Employee Attrition using Machine Learning

Abstract

Employee attrition is a major cost to an organization. Some costs are tangible such as training expenses and the time it takes from when an employee starts to when they become a productive member. However, the most important costs are intangible, such as new product ideas, great project management, or customer relationships. Employee attrition control is critical to the long term health and success of any organization. An organization is only as good as its employees, and these people are the true source of its competitive advantage. Accurate predictions enable organizations to take action for the retention of employees. This project aims to use different supervised classifiers to make predictions, and chooses the most accurate one.