Predicting Academic Performance of Tertiary Students using Classification Algorithm
Sujith Jayaprakash1, Jaiganesh V2
1Sujith Jayaprakash, Research Scholar, Department of PG & Research Dr. N.G.P Arts & Science College, Coimbatore, India.
2Dr. Jaiganesh, V., Assistant Professor, Department of PG & Research Dr. N.G.P Arts & Science College, Coimbatore, India.
Manuscript received on 21 March 2019 | Revised Manuscript received on 25 March 2019 | Manuscript published on 30 July 2019 | PP: 6558-6561 | Volume-8 Issue-2, July 2019 | Retrieval Number: B2716078219/19©BEIESP | DOI: 10.35940/ijrte.B2716.078219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Classification algorithms have paved the way for several recommender systems in the field of Medicine, Entertainment, Politics, Education, etc. Recently there is a growing interest among researchers to analyze or predict the academic progression of students from High Schools to Tertiary Education. Better performance of students will directly reciprocate in the growth of an institution. Hence, setting up a supervised learning system will act as a gauge to provide a benchmark education. This paper aims to recommend a system based on a predictive model which will aid the institution to measure the performance of students based on various parameters.
Index Terms: Academic Progression of Students; Classification Algorithm, Machine Learning, Naïve Bayes Algorithm, Recommender System, Supervised Learning
Scope of the Article: Classification