• Darshna Dalvadi

Employee attrition is the percentage of employees who leave a company and are replaced by new employees. A high rate of attrition in an organization leads to increased recruitment, hiring and training costs. It is extremely demanding and trending research area in today’s working culture. Most of the employees leaves the job due to dissatisfaction or low income or company political issue or reason can be enormous. This paper not only predicts the stay of an employee in a company but it also provides the key criteria which lead the employee to leave the job. Predicting Attrition has become essential need of Human Resources (HR) in many companies. Machine learning (ML) developments have made it possible to obtain both improved forecasting performance and clearer explanations of what essential features are associated to employee attrition. In this project, various machine learning approach for employee attrition prediction will be implemented to find out the best solution among them. This paper initially provides comparative analysis of various ML approaches for employee attrition prediction and then gives the best solution for employee attrition prediction and also provides critical features linked to employee attrition.

Attrition, Prediction, Random forest, Logistic regression, ML

"Employee Attrition Prediction using Various Machine Learning Algorithms", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 12, page no.1411-1416, December-2018, Available :http://www.jetir.org/papers/JETIR1812E03.pdf

"Employee Attrition Prediction using Various Machine Learning Algorithms", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 12, page no. pp1411-1416, December-2018, Available at : http://www.jetir.org/papers/JETIR1812E03.pdf