Comparative Study Of The Machine Learning Techniques For Predicting The Employee Attrition
Keywords:
work role, overtime, economic cost, logistic regression, lasso categorization, ridge classification,random forests.Abstract
In HR Analytics, employee attrition was one of the most significant business issues. Companies spend a lot of money on employee training because they know how much money they will bring in in the future. When an employee leaves the organization, the
company suffers a loss of economic cost. In the mass recruiting industry, attrition is very high. We have chosen a sample of IBM USA's employee information for this research. Using the data value idea, we discovered that employee attributes such as work role, overtime, and job level have a significant impact on turnover.
References
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D. K. Srivastava and P. Nair, “Employee attrition analysis using predictive techniques,” in Proc. Int. Conf. Inf. Commun. Technol. Intell. Syst., Springer, Cham, pp. –, 2017.
S. S. Alduayj and K. Rajpoot, “Predicting employee attrition using machine learning,” in Proc. Int. Conf. Innov. Inf. Technol. (IIT), pp. –, 2018.
