Prediction of Employee Turnover using Machine Learning

IT Industry is very competitive and committed to finding new practices for the future. It is important to overcome business challenges to sustain in the competition. The employee turnover is a systematic issue in most industries from past few years. As employees tend to leave the company when they find better opportunities incurs a loss in terms of money, time and resources and must be replaced with their equivalent skills. The productivity and the profitability of the organizations depends on trained and skilled employees, hence turnover rates need to be monitored In this work, we forecast the employee turnover rates of the organization using machinelearning algorithms. Data collected on employee work profile. Well-reviewed and Industry accepted algorithms like Naive Bayes, random forest and logistic regression are applied. Result taken from the model giving highest accuracy. Our model demonstrates a strong feedback accumulated from employees, which act as a token of exercise to evaluate individual’s interests. With help of such predictive models, organization can overcome the business challenges and achieve competitive success.