Forecasting Modelling for Campus Placement: A Comparative Study of Machine Learning Algorithms

Shivangi Srivastava; Vishal Bharati

doi:10.55524/ijirem.2026.13.2.12

Abstract

In this research paper, we investigate the use of machine learning algorithms to predict campus placement outcomes. Our study uses a dataset that includes various attributes of students, such as academic performance, background information, and employability test scores. By conducting extensive data pre-processing, exploratory data analysis (EDA), and predictive modelling techniques, we aim to create accurate predictive models and compare the performance of different algorithms. In addition, we have developed a recommendation system that offers actionable insights to students based on the model predictions.The main objective of this placement prediction model is to develop skills in students, primarily by improving their academic performance and exam results. There by increasing their chances of getting placed. The use and study of such machine learning and AI-based models also helps colleges and educational institutions improve their placement departments and develop new technologies. This type of study also assists the faculty of these institutions in training students accordingly. This research helps institutions understanding students learning pace and skill development track their progress and determine the requirements of recruiting companies or organizations, ensuring that these needs are met.

Keywords

Campus Placement Prediction, Machine Learning, Educational Data Mining, Student Employability Forecasting, Predictive Analytics, Classification Models

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Cites this article as

S. Srivastava, V. Bharati, "Forecasting Modelling for Campus Placement: A Comparative Study of Machine Learning Algorithms", International Journal of Innovative Research in Engineering and Management (IJIREM), Vol-13, Issue-2, Page No-82-87, 2026. Available from: https://doi.org/10.55524/ijirem.2026.13.2.12

Corresponding Author

Shivangi Srivastava

M.Tech Scholar, Department of Computer Science and Engineering, Suyash Institute of Information Technology, Gorakhpur, India

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