Published Paper Details:

Employee attrition is one of the most serious issues facing companies today. When long-term employees leave the company, it impacts the company's relationship with the customer, which in turn affects the company's revenue if the person who replaces the previous employee is unable to maintain a good rapport with the client. These studies evaluate the employee attrition rate through relevant factors such as Job Role, overtime, and job level, which all have a significant impact on attrition. The study includes a survey of various classification techniques, such as logistic regression, ridge classification, decision trees, and random forests, to forecast the likelihood of attrition of every new employee. A systematic and comprehensive evaluation approach is used to assess the performance of each of these supervised machine learning methods. This survey will assist human resource managers in identifying individuals who are likely to leave the firm and forecasting the reasons for their choice, allowing HR managers to design a retention strategy or seek a replacement..