Early grade prediction using profile data

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2020.

Manylion Llyfryddiaeth
Prif Awduron:	Iqbal, Sumaiya, Muntaha, Mahjabin, Natasha, Jerin Ishrat, Sakib, Dewan
Awduron Eraill:	Majumdar, Mahbubul Alam
Fformat:	Traethawd Ymchwil
Iaith:	en_US
Cyhoeddwyd:	Brac University 2021
Pynciau:	Machine Learning Algorithms Linear Regression Decision Tree Regression Gaussian Na¨ıve Bayes Decision Tree Classifier Feature Importance ChiSquare
Mynediad Ar-lein:	http://hdl.handle.net/10361/14462

id	10361-14462
record_format	dspace
spelling	10361-144622022-01-26T10:08:22Z Early grade prediction using profile data Iqbal, Sumaiya Muntaha, Mahjabin Natasha, Jerin Ishrat Sakib, Dewan Majumdar, Mahbubul Alam Department of Computer Science and Engineering, Brac University Machine Learning Algorithms Linear Regression Decision Tree Regression Gaussian Na¨ıve Bayes Decision Tree Classifier Feature Importance ChiSquare This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2020. Cataloged from PDF version of thesis. Includes bibliographical references (pages 44-47). Universities are reputable institutions for higher education and therefore it is crucial that the students have satisfactory grades. Quite often it is seen that during the first few semesters many students dropout from the universities or have to struggle in order to complete the courses. One way to address the issue is early grade prediction using Machine Learning techniques, for the courses taken by the students so that the students in need can be provided special assistance by the instructors. Machine Learning Algorithms such as Linear Regression, Decision Tree Regression, Gaussian Na¨ıve Bayes, Decision Tree Classifier have been applied on the data set to predict students’ results and to compare their accuracy. The evaluated profile data have been collected from the students of 10th semester or above of the Computer Science department, BRAC University, Dhaka, Bangladesh. The Decision Tree Classifier technique has been found to perform the best in predicting the grade, closely followed by Decision Tree Regression and Linear Regression has performed the worst. Sumaiya Iqbal Mahjabin Muntaha Jerin Ishrat Natasha Dewan Sakib B. Computer Science 2021-06-01T17:33:44Z 2021-06-01T17:33:44Z 2020 2020-04 Thesis ID: 16101189 ID: 16101246 ID: 19241035 ID: 19341009 http://hdl.handle.net/10361/14462 en_US Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 47 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	en_US
topic	Machine Learning Algorithms Linear Regression Decision Tree Regression Gaussian Na¨ıve Bayes Decision Tree Classifier Feature Importance ChiSquare
spellingShingle	Machine Learning Algorithms Linear Regression Decision Tree Regression Gaussian Na¨ıve Bayes Decision Tree Classifier Feature Importance ChiSquare Iqbal, Sumaiya Muntaha, Mahjabin Natasha, Jerin Ishrat Sakib, Dewan Early grade prediction using profile data
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2020.
author2	Majumdar, Mahbubul Alam
author_facet	Majumdar, Mahbubul Alam Iqbal, Sumaiya Muntaha, Mahjabin Natasha, Jerin Ishrat Sakib, Dewan
format	Thesis
author	Iqbal, Sumaiya Muntaha, Mahjabin Natasha, Jerin Ishrat Sakib, Dewan
author_sort	Iqbal, Sumaiya
title	Early grade prediction using profile data
title_short	Early grade prediction using profile data
title_full	Early grade prediction using profile data
title_fullStr	Early grade prediction using profile data
title_full_unstemmed	Early grade prediction using profile data
title_sort	early grade prediction using profile data
publisher	Brac University
publishDate	2021
url	http://hdl.handle.net/10361/14462
work_keys_str_mv	AT iqbalsumaiya earlygradepredictionusingprofiledata AT muntahamahjabin earlygradepredictionusingprofiledata AT natashajerinishrat earlygradepredictionusingprofiledata AT sakibdewan earlygradepredictionusingprofiledata
_version_	1814307484752412672

Early grade prediction using profile data

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