Abstract
When you think about the global situation, there is a sea of opportunity for skilled people all over the globe, and for a given opportunity, the workers shift from one company to other that leads to a high attrition rate within the company. Nowadays, employee attrition is treated as a severe problem by all the companies due to the negative impact on productivity at work and on completing company goals and vision in time. To deal with this problem, companies are now relying on machine learning methods to predict employee attrition rate. These methods work on products based on employee data analysis and the degree of prediction by the models. With accurate results, all the companies may take necessary actions in a timely manner for retaining or dismissing the staff. The system currently in use is the human resource’s data system which does not work well in predicting how efficient the worker will be to the institution in future. These models that are used by the companies are now outdated and do not help them in successfully making decisions; in this paper, we have used modern machine learning algorithm models for predicting employee attrition that is employee’s plan to either leave or continue working within the organization based on available huge data set to give more close results.
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Aggarwal, S., Singh, M., Chauhan, S., Sharma, M., Jain, D. (2022). Employee Attrition Prediction Using Machine Learning Comparative Study. In: Reddy, A.N.R., Marla, D., Favorskaya, M.N., Satapathy, S.C. (eds) Intelligent Manufacturing and Energy Sustainability. Smart Innovation, Systems and Technologies, vol 265. Springer, Singapore. https://doi.org/10.1007/978-981-16-6482-3_45
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DOI: https://doi.org/10.1007/978-981-16-6482-3_45
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