A Framework for Student Academic Performance Using Naive Bayes Classification Technique
Y Divyabharathi, P Someswari
Corresponding Author : Y Divyabharathi
Department of Computer Science Engineering,, GMR Institute of Technology, Andhra Pradesh, INDIA.
Email ID : email@example.com
Received : 2018-04-25 Accepted : 2018-06-05 Published : 2018-06-05
Abstract : The real fact in the education institute is the significant growth of the educational data. Data mining techniques are used to extract the useful information and to predict the student academic performance. The main aim of this paper is to construct predictive model for student academic performance. As there are many classification techniques are available, in this paper naive bayes classification technique is used. This paper presents and analyses the experience of applying certain data mining methods and techniques on student data in order to prevent academic risk and desertion.
Keywords : Data Mining, Predictive modeling, Academic risk prevention, Academic Performance, Educational data mining.
Citation : Y Divyabharathi et al. (2018). A Framework for Student Academic Performance Using Naive Bayes Classification Technique, J. of Advancement in Engineering and Technology, V6I3.08. DOI : 10.5281/zenodo.1277183
Copyright : © 2018 Y Divyabharathi . This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Journal of Advancement in Engineering and Technology
ISSN : 2348-2931
Volume 6 / Issue 3
ScienceQ Publishing GroupDownload Article
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