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Reseach Article

Analysis of Machine Learning through Support Vector Machine: Catalyst

by Pooja Shrimali, K. Venugopalan
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 100 - Number 6
Year of Publication: 2014
Authors: Pooja Shrimali, K. Venugopalan
10.5120/17532-8105

Pooja Shrimali, K. Venugopalan . Analysis of Machine Learning through Support Vector Machine: Catalyst. International Journal of Computer Applications. 100, 6 ( August 2014), 42-46. DOI=10.5120/17532-8105

@article{ 10.5120/17532-8105,
author = { Pooja Shrimali, K. Venugopalan },
title = { Analysis of Machine Learning through Support Vector Machine: Catalyst },
journal = { International Journal of Computer Applications },
issue_date = { August 2014 },
volume = { 100 },
number = { 6 },
month = { August },
year = { 2014 },
issn = { 0975-8887 },
pages = { 42-46 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume100/number6/17532-8105/ },
doi = { 10.5120/17532-8105 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:29:16.693946+05:30
%A Pooja Shrimali
%A K. Venugopalan
%T Analysis of Machine Learning through Support Vector Machine: Catalyst
%J International Journal of Computer Applications
%@ 0975-8887
%V 100
%N 6
%P 42-46
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper investigates the use of support vector machine (SVM) in machine learning. The purpose of this study is to experiment of SVM in e-learning methodology. Main constituent of this research is to innovate and implement pedagogical hypermedia document. In the article [19] artificial neural network (ANN) has been used to test learners learning capabilities, which is now being replaced by SVM in the present article to understand statistical analysis of learner's knowledge level. By this experiment it is suggested that this methodology is over and above ANN which is used as mathematical and statistical results.

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Index Terms

Computer Science
Information Sciences

Keywords

Machine learning SVM adaptive e-learning learning objects