ISSN 2394-5125

    Machine Learning Framework for Prediction of Admission in Engineering College (2023)

    Dr. B. Subba Reddy, B. Pallavi, B. Shruthi, T. Rohini
    JCR. 2023: 133-143


    Utilizing machine learning (ML), enormous amounts of information can be re-evaluated and discover patterns that might not be immediately noticeable or recognizable to humans. ML strategies have increasingly been used to assess educational data such as student class performance. In the pursuit of the academic well-being of students, the utilization of neoteric technologies such as data mining, data management, and ML has increased. The idea of extracting undisclosed information from many raw databases is called data mining. Consequently, the exploration of knowledge acquisition relates to predictive ML models and subsequent decision-making. State-of-the-arts of data mining and ML have become more acceptable in predicting student examination evaluations such as grades, achievement, etc. Generally, conventional data mining for educational data analysis aimed at solving problems in an educational context can be described as educational data mining. Currently, intelligent computer-based methods such as artificial intelligence and data mining have been successfully applied to improve people's daily lives. A couple of million students participate in the bachelor's entrance examination at government-run universities each year in India. Nevertheless, only a few thousand are admitted after this competitive examination. In some cases, it was observed that many candidates struggled hard during this period. However, they could not get admission to a public university in India, resulting in an unforeseeable future. Numerous factors could be behind their unsuccessful admission to a public university, such as family circumstances, frustration, admission test anxiety, etc. However, Indian students need admission to a public university because private university education costs are too high for middle-income and low-income families. In contrast, the government primarily covers public university costs. Therefore, this project implements the prediction of college admission for engineering or college students using machine learning algorithm.


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    Volume & Issue

    Volume 10 Issue-1