文章基本信息

标题：Machine Learning Techniques for Prediction of Subject Scores: A Comparative Study
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作者：Mamta Singh ; Dr. Jyoti Singh
期刊名称：International Journal of Computer Science and Network
印刷版ISSN：2277-5420
出版年度：2013
卷号：2
期号：4
页码：77-80
出版社：IJCSN publisher
摘要：In this paper, a novel method is proposed so as to predict thesubject wise academic performance of the Engineering students.This study describes the prediction of subject scores in ongoingcourses by analyzing subject preludes of previous semester. Inthis study we try to predict the individual subject scores forongoing courses while comparing two classification techniquesi.e. Naive Bayesian and C4.5 Decision tree classifier. This pieceof work adheres to most critical aspect of Quality objectives ofAcademia i.e. finding students’ academic performances for theirongoing courses well before they face their End semesterExamination. Unlike the recent research trends that focused onpredicting overall grading of students during their studies, thispaper orients itself in identifying students grasping levelssubject wise. It was found that from study, that obtainedaccuracy figure was higher in C4.5 Decision tree classifier thanNaïve Bayes
关键词：Academic Performance; C4.5; Naïve Bayesian;classification; Analytics; Subject prelude.