Please use this identifier to cite or link to this item:
https://dl.ucsc.cmb.ac.lk/jspui/handle/123456789/4597
Title: | Student Result Predictor Using Machine Learning Techniques |
Authors: | Thilakaratne, P.H. |
Keywords: | Machine Learning Student Result Predictor Semester Result Predictor Support Vector Machine Decision Tree Naïve Bayes |
Issue Date: | 10-Jun-2022 |
Abstract: | Education is one of the most important aspect in human life. As human all of us spending twelve to thirteen years at schools and then passing through to higher education institutes such as universities. In universities student face exams and some of them get through it and others get stuck. This study will predict student academic performance with the help of machine learning algorithms. This study will discuss about four classification algorithms such as Decision tree classifier, Support Vector Machine Classifier, Naïve Bayes and Random Forest classifier. This study will address which would be the optimum algorithm can be used to predict student results under identified parameters. |
URI: | https://dl.ucsc.cmb.ac.lk/jspui/handle/123456789/4597 |
Appears in Collections: | 2021 |
Files in This Item:
File | Description | Size | Format | |
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2018 BA 035.pdf | 2.69 MB | Adobe PDF | View/Open |
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