Journal of Information Organization


Vol No. 9 ,Issue No. 4 2019

Prediction of Employee Retention using Cassandra and Ensemble Learning
Shubham Karande, Ajay Shelake, Sivagami M, Sharon Sophia
VIT University, India
Abstract: Employee turnover is now becoming a major problem in IT organizations, telecommunications and many other industries. Why employees leave the organization? is the question raising among many HR managers. Employees are the most important assets of an organization. Hiring new will always take more efforts and cost rather than retaining the old ones. This paper focuses on finding the key features of voluntary employee turnover and how they can be overcome well before time. The problem is to classify whether an employee will leave or stay. Data is taken from Kaggle. The proposed work will uses ensemble learning to solve the problem, rather than focusing on a single classifier algorithm it will combine weak learning algorithms to get a better ensemble model. We have used Cassandra to store the data in the form of table and retrieving data to perform machine algorithm on them.
Keywords: Employee Retention, Cassandra, Classification, Ensemble Learning, Machine Learning Prediction of Employee Retention using Cassandra and Ensemble Learning
DOI:https://doi.org/10.6025/jio/2019/9/4/134-140
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