Employee Churn Forecast Study Based on Clustering Analysis and Machine Learning Models

Abstract

In recent years, company is necessary to forecast churn customers in order to retain customers. Customer attrition is a crucial problem that every business must make the utmost effort to prevent. Employee churn or loss of workers would be similar to customer attrition, but the effect of losing a significant client for the company would probably be more traumatic while the effects of finding good employees instead of lost employees, as well as the expense of in-service training that could be offered to new employees. This paper finds out the groups of employees who left by using k-mean clustering and then predict the employee churn by using machine learning models. Finally, this paper assesses the performance of employee churn prediction and then compares the result with high accuracy. The purpose of this study is to predict employee churn, which allows the company to take the required steps.