Forecasting Employees Churn Analysis using Selected Machine Learning Models

In the context of a business setting, the process of analysing and measuring the rate at which workers leave a company, as well as determining which people are most likely to depart, is referred to as employee churn analytics. This kind of analysis may also be used to anticipate which individuals are most likely to leave. Because of the continuously shifting requirements in many businesses, workers often find themselves in a position to pursue new employment opportunities. Because of this, companies are obligated to look for potential successors who already have the experience and education necessary to properly carry out the tasks that are involved with the role. In the event that a bottleneck occurs, the corporate sector will be required to make extra financial investments in order to return the organization’s workday to its previously established pattern of operation. During the course of investigation, the study analysis number of machine learning (ML) algorithms that concentrate on reviewing the history of an employee and evaluating a variety of characteristics in an efficient way. The purpose of these methods is to determine whether or not the employee will continue working for the firm or will at some point in the future depart the business.