A Comparative analysis of various Machines learning algorithm based predictive models for employability prediction of Indian Engineering Students

  • Neha Eknath Vekhande, Dr. Debirupa Hore
Keywords: Machine Learning, Ensemble learning, Prediction Model, Student placement prediction, Higher Education system.

Abstract

Early employability or job readiness prediction is an important technique in benefit of the student as well as educational organization. Based on the accurate prediction the constructive action can be taken. This paper presents a comparative analysis of different machine learning models for predicting the employability of the students learned upon the employability and personality test data set. The comparative analysis of the models shows that the ensemble models outperform the single models. Applying 10-fold cross validation on all 10 models the AdaBoost-Ensemble model showed better accuracy. The study proposes the optimization-based weighted ensemble learning prediction model to predict the employability outcomes for Indian engineering graduates.

Published
2021-10-27
How to Cite
Dr. Debirupa Hore, N. E. V. (2021). A Comparative analysis of various Machines learning algorithm based predictive models for employability prediction of Indian Engineering Students. Design Engineering, 2770-2786. Retrieved from http://www.thedesignengineering.com/index.php/DE/article/view/5756
Section
Articles