Predictive Analytics for Employee Promotion Using Machine Learning: A Comparative Study of Ensemble Methods

Authors: Jwalin Thaker

DOI: https://doi.org/10.5281/zenodo.14981237

Short DOI: https://doi.org/g868r8

Country: USA

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Abstract: In any business organization, there are several positions for employees to fill. These positions are sometimes based on hierarchy where employees who are in top level positions are more experienced and have higher skill level than the employees who work under them. Employees who are in the lower levels, however, can get promoted to a higher position by the organization if their work efforts are recognized by the organization. The role of analyzing, screening, recruiting and promoting workers in a company is done by the company’s Human Resources (HR) manager. This project is developed to assist a HR manager in the tasks mentioned above by creating a model using different machine learning algorithms such as Support Vector Machines (SVM), Artificial Neural Networks (ANN), Random Forest Regressor and Decision Trees.

Keywords: Machine Learning, Human Resources Analytics, Employee Promotion, Ensemble Methods, Comparative Analysis

Paper Id: 232226

Published On: 2019-12-08

Published In: Volume 7, Issue 6, November-December 2019

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