Evaluating student’s performance using k- mean clustering

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dc.contributor.authorShahid Eqbal
dc.contributor.authorAyush Singh
dc.contributor.authorBalkrishna Pandey
dc.contributor.authorDeepa Singh
dc.date.accessioned2024-11-05T12:23:55Z
dc.date.available2024-11-05T12:23:55Z
dc.date.issued2024-10-28
dc.description.abstractThe analysis and evaluation of a student's academic achievement are now difficult tasks for the academic community to do. Classifying student achievement is a difficult scientific task in the actual world. Thus, a system to evaluate students’ performance utilizing a deterministic model and the k-means clustering algorithm is described in this study. The analysis findings will help academic planners determine how well students performed over a particular semester and what initiatives they need to take to raise students’ performance.
dc.identifier.citationShahid E., Ayush S., Balkrishna P. & Deepa S. (2023). “Evaluating student’s performance using k- mean clustering". In Proceedings of the International Conference on Artificial Intelligence and Robotics (MIRG-ICAIR 2023), pp. 127-132, MIRG
dc.identifier.isbn978-978-767-697-4
dc.identifier.urihttps://ir.unilag.edu.ng/handle/123456789/13032
dc.language.isoen
dc.publisherMIRG
dc.relation.ispartofseriesMIRG-ICAIR 2023
dc.titleEvaluating student’s performance using k- mean clustering
dc.typeArticle
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