Undergraduate Student’s Campus Placement Determination Using Logistic Regression Analysis for Predicted Probabilities on Uncertain Dataset

Authors

  • Chandra Sekhar K. Research Scholar, Department of Information Technology, Annamalai University, Annamalai Nagar, Chidambaram-608002, India https://orcid.org/0000-0001-7052-3008
  • K. Santhosh Kumar Assistant Professor, Department of Information Technology, Annamalai University, Annamalai Nagar, Chidambaram-608002, India

Keywords:

Logistic Regression; Undergraduate; Placement; Prediction; Probabilities; Coefficients; Features

Abstract

Undergraduate students in technical institutions aim to secure a placement within four years of the Course. Many factors impact student placement chances. Analysis and understanding of the factors influencing the student chances could change the orientation of coming generations towards education. This work is a clear understanding of the placement factors affecting students' chances and an illustration of Logistic Regression. In this paper, Logistic Regression accurately predicts which factors influence graduate placement opportunities. Using a uncertain dataset that comprises more than 1000 students' information to find predictions. We have shown the predicted probabilities of each student who can secure a job along with actual job status. The prediction probability calculations and machine learning model predictions are compared and found to be equal. The approach can be used to guide the coming generation of students to have a note of factors that could influence their placement chances.

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A complete outline of linear regression application on the Graduate Placement uncertain dataset.

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Published

19.12.2022

How to Cite

Chandra Sekhar K., & K. Santhosh Kumar. (2022). Undergraduate Student’s Campus Placement Determination Using Logistic Regression Analysis for Predicted Probabilities on Uncertain Dataset. International Journal of Intelligent Systems and Applications in Engineering, 10(2s), 14–20. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/2355

Issue

Vol. 10 No. 2s (2022)

Section

Research Article

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