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Prediction of Employee Retention using Cassandra and Ensemble Learning
Karande S, Shelake A, ,
Published in Digital Information Research Foundation
Volume: 9
Issue: 4
Pages: 508 - 512
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. © BEIESP.
About the journal
JournalJournal of Information Organization
PublisherDigital Information Research Foundation
Open AccessNo