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Analyzing the Student Performance using Classification Techniques to find the Better Suited Classifier

by Sherine Dominick, T. Abdul Razak
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 104 - Number 4
Year of Publication: 2014
Authors: Sherine Dominick, T. Abdul Razak
10.5120/18187-9092

Sherine Dominick, T. Abdul Razak . Analyzing the Student Performance using Classification Techniques to find the Better Suited Classifier. International Journal of Computer Applications. 104, 4 ( October 2014), 1-3. DOI=10.5120/18187-9092

@article{ 10.5120/18187-9092,
author = { Sherine Dominick, T. Abdul Razak },
title = { Analyzing the Student Performance using Classification Techniques to find the Better Suited Classifier },
journal = { International Journal of Computer Applications },
issue_date = { October 2014 },
volume = { 104 },
number = { 4 },
month = { October },
year = { 2014 },
issn = { 0975-8887 },
pages = { 1-3 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume104/number4/18187-9092/ },
doi = { 10.5120/18187-9092 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:35:15.636709+05:30
%A Sherine Dominick
%A T. Abdul Razak
%T Analyzing the Student Performance using Classification Techniques to find the Better Suited Classifier
%J International Journal of Computer Applications
%@ 0975-8887
%V 104
%N 4
%P 1-3
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Educational institutions are producing talented and intelligent students and workers, but when we consider quality and equity of the student's progress in his career, it is still a challenge or a question to be answered. These institutions focus on quality in education. Every year a huge number of students graduate from colleges and universities, with respect to the data collected from the feedback of students, classification a data mining technique is applied to it. It is a step to analyze the factors affecting the academic performance of students in order to evaluate the current student performance and take efficient steps in the prediction of the most likely occurring relationships between the various aspects of learning and to enhance the quality of education in future and help the educational planners to plan accordingly.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Data Mining Classification Student Performance Prediction.

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