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Reseach Article

A Heart Disease Prediction Model using SVM-Decision Trees-Logistic Regression (SDL)

by Mythili T., Dev Mukherji, Nikita Padalia, Abhiram Naidu
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 68 - Number 16
Year of Publication: 2013
Authors: Mythili T., Dev Mukherji, Nikita Padalia, Abhiram Naidu
10.5120/11662-7250

Mythili T., Dev Mukherji, Nikita Padalia, Abhiram Naidu . A Heart Disease Prediction Model using SVM-Decision Trees-Logistic Regression (SDL). International Journal of Computer Applications. 68, 16 ( April 2013), 11-15. DOI=10.5120/11662-7250

@article{ 10.5120/11662-7250,
author = { Mythili T., Dev Mukherji, Nikita Padalia, Abhiram Naidu },
title = { A Heart Disease Prediction Model using SVM-Decision Trees-Logistic Regression (SDL) },
journal = { International Journal of Computer Applications },
issue_date = { April 2013 },
volume = { 68 },
number = { 16 },
month = { April },
year = { 2013 },
issn = { 0975-8887 },
pages = { 11-15 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume68/number16/11662-7250/ },
doi = { 10.5120/11662-7250 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:28:01.097522+05:30
%A Mythili T.
%A Dev Mukherji
%A Nikita Padalia
%A Abhiram Naidu
%T A Heart Disease Prediction Model using SVM-Decision Trees-Logistic Regression (SDL)
%J International Journal of Computer Applications
%@ 0975-8887
%V 68
%N 16
%P 11-15
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The early prognosis of cardiovascular diseases can aid in making decisions to lifestyle changes in high risk patients and in turn reduce their complications. Research has attempted to pinpoint the most influential factors of heart disease as well as accurately predict the overall risk using homogenous data mining techniques. Recent research has delved into amalgamating these techniques using approaches such as hybrid data mining algorithms. This paper proposes a rule based model to compare the accuracies of applying rules to the individual results of support vector machine, decision trees, and logistic regression on the Cleveland Heart Disease Database in order to present an accurate model of predicting heart disease.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Heart disease support vector machine (SVM) logistic regression decision trees rule based approach