Leveraging the accuracy of the Employee Attrition model: A Machine Learning Approach

• Author(s): Tanmay Dhamdhere ; Dr. Vipul Dalal
• Paper ID: 1702543
• Page: 30-33
• Published Date: 06-12-2020
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 4 Issue 6 December-2020

Abstract

Employee attrition is a process in which the employees working in a company quits his/her job due to various reasons. For instances due to retirement, sacking from the organization or personal reasons. The task of churning the employee is an hectic one, as there are no fixed pattern or formula which can give an accurate prediction of whom to churn. But when implemented, It can certainly lead to an winning situation for the companies. The companies will be largely benefitted by the attrition of the employees as it can significantly reduce the cost of the labors, also it can bring an overall changes which can positively affect the company’s growth. Employees are the backbone for any company to bloom. There are certain factors such as age, increment, pay and many more which comes in picture for attrition of the employee. Using proper methodology and planning, it will be easy for a company to churn out the wrong employee and to proliferate their progress. In this paper, we have proposed a suitable method, which uses the techniques related to Machine Learning to yield an accuracy of 81.31%. Using this strategy, an overall accuracy of 96% can be achieved which can potentially help the companies towards its goal.

Keywords

Machine Learning, attrition, churn, goal

Citations

IRE Journals:
Tanmay Dhamdhere , Dr. Vipul Dalal "Leveraging the accuracy of the Employee Attrition model: A Machine Learning Approach " Iconic Research And Engineering Journals Volume 4 Issue 6 2020 Page 30-33

IEEE:
Tanmay Dhamdhere , Dr. Vipul Dalal "Leveraging the accuracy of the Employee Attrition model: A Machine Learning Approach " Iconic Research And Engineering Journals, 4(6)