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Analysis of Classification Algorithms Applied to Hepatitis Patients

by T. Karthikeyan, P. Thangaraju
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 62 - Number 15
Year of Publication: 2013
Authors: T. Karthikeyan, P. Thangaraju
10.5120/10157-5032

T. Karthikeyan, P. Thangaraju . Analysis of Classification Algorithms Applied to Hepatitis Patients. International Journal of Computer Applications. 62, 15 ( January 2013), 25-30. DOI=10.5120/10157-5032

@article{ 10.5120/10157-5032,
author = { T. Karthikeyan, P. Thangaraju },
title = { Analysis of Classification Algorithms Applied to Hepatitis Patients },
journal = { International Journal of Computer Applications },
issue_date = { January 2013 },
volume = { 62 },
number = { 15 },
month = { January },
year = { 2013 },
issn = { 0975-8887 },
pages = { 25-30 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume62/number15/10157-5032/ },
doi = { 10.5120/10157-5032 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:11:53.516637+05:30
%A T. Karthikeyan
%A P. Thangaraju
%T Analysis of Classification Algorithms Applied to Hepatitis Patients
%J International Journal of Computer Applications
%@ 0975-8887
%V 62
%N 15
%P 25-30
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper mainly deals with various classification algorithms namely, Bayes. NaiveBayes, Bayes. BayesNet, Bayes. NaiveBayesUpdatable, J48, Randomforest, and Multi Layer Perceptron. It analyzes the hepatitis patients from the UC Irvine machine learning repository. The results of the classification model are accuracy and time. Finally, it concludes that the Naive Bayes performance is better than other classification techniques for hepatitis patients.

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Index Terms

Computer Science
Information Sciences

Keywords

Naive bayes Multi Layer Perceptron Random Forest J48

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