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Reseach Article

Predicting Student’s Performance using Machine Learning

by Vrushali A. Sungar, Pooja D. Shinde, Monali V. Rupnar
Communications on Applied Electronics
Foundation of Computer Science (FCS), NY, USA
Volume 7 - Number 11
Year of Publication: 2017
Authors: Vrushali A. Sungar, Pooja D. Shinde, Monali V. Rupnar

Vrushali A. Sungar, Pooja D. Shinde, Monali V. Rupnar . Predicting Student’s Performance using Machine Learning. Communications on Applied Electronics. 7, 11 ( Dec 2017), 11-15. DOI=10.5120/cae2017652730

@article{ 10.5120/cae2017652730,
author = { Vrushali A. Sungar, Pooja D. Shinde, Monali V. Rupnar },
title = { Predicting Student’s Performance using Machine Learning },
journal = { Communications on Applied Electronics },
issue_date = { Dec 2017 },
volume = { 7 },
number = { 11 },
month = { Dec },
year = { 2017 },
issn = { 2394-4714 },
pages = { 11-15 },
numpages = {9},
url = { },
doi = { 10.5120/cae2017652730 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2023-09-04T20:01:52.544903+05:30
%A Vrushali A. Sungar
%A Pooja D. Shinde
%A Monali V. Rupnar
%T Predicting Student’s Performance using Machine Learning
%J Communications on Applied Electronics
%@ 2394-4714
%V 7
%N 11
%P 11-15
%D 2017
%I Foundation of Computer Science (FCS), NY, USA

Education plays vital role in a student’s life. While choosing any field, number of options available in front of student. Student’s marks, aptitude, family background, educational environment are main essential factors while selecting a career path and these factors act as a training set to the learning system for classification. With time educational records are accumulating and increasing rapidly. To handle this data along with new features without forgetting previously learnt knowledge, incremental learning technique is introduced by machine learning. Incremental learning algorithm handles previous knowledge to take future decisions and update the system. Knowledge is represented by combining different classifiers for identification of student’s features for his/her career growth. In this paper, ensemble technique is used with incremental algorithm for student’s career choice and results over real world data sets are used to validate the effectiveness of this method.

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Index Terms

Computer Science
Information Sciences


Incremental learning classifiers machine learning knowledge