Campus Placement Prediction using Machine Learning

Authors

  • Vemulapalli Nageswara Rao, P. Dhanalakshmi

Keywords:

Campus Placement, Placement Prediction, Machine Learning, Supervised Learning, Student Employability, Classification Algorithms, Data Pre-processing, Feature Selection, Model Evaluation, Predictive Analytics.

Abstract

The Smart Campus Placement System is an online system constructed with the aim of easing the process of students, companies and TPOs during the placement process. Companies can post job openings and conduct tests, and students can apply, take tests, and get results depending on the performance. A smart job suggestion feature with the help of the K-Nearest Neighbors (KNN) algorithm is aimed at providing students with an opportunity to get corresponding jobs on the basis of their skills and academics. The system also employs machine learning to predict chances of placement based on grades, work experience, test scores among others. Various models such as Decision Trees and Random Forest were tested for accuracy. This helps the students identify the strengths and therefore excel while institutions can modify trainings and support. On the whole, the system makes placements smarter, faster, and their occurrence is consequential. The proposed method helps to college students as well as college faculty to take smart decision.

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References

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Published

20.12.2022

How to Cite

Vemulapalli Nageswara Rao. (2022). Campus Placement Prediction using Machine Learning. International Journal of Intelligent Systems and Applications in Engineering, 10(4), 771–777. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/7585

Issue

Vol. 10 No. 4 (2022)

Section

Research Article

License

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