Predicting Employee Attrition using Supervised Learning Classification Models

Abstract

Employee attrition phenomenon is one of the most well-known problems in the field of human resources management. This happens when an employee decides to leave his post due to many personal and professional reasons. When a well trained and adapted human resource leaves the company, it becomes very difficult to fill the gap instantly. Therefore, it impacts directly the efficiency of the group. Many researches in the HR management have been carried out to deal with the employee attrition problem by reducing the its rate within companies. The aim of this paper, is to provide a model that can predict whether an employee might voluntarily make the decision to leave its position using the supervised classification and the machine learning algorithms. We also described some professional and personal factors that could influence the employee attrition rate. Experimental results on a real data provided by IBM demonstrates the efficiency of the proposed models.

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