A Heart Disease Prediction Model using Logistic Regression By Cleveland DataBase

M. Sai Chaitanya; G. Sai Kiran; K. Sandhya Rani

Title:
A Heart Disease Prediction Model using Logistic Regression By Cleveland DataBase

Authors:
K. Sandhya Rani | M. Sai Chaitanya | G. Sai Kiran
DOI:
https://doi.org/10.31142/ijtsrd11402

Cite This Article :

K. Sandhya Rani | M. Sai Chaitanya | G. Sai Kiran "A Heart Disease Prediction Model using Logistic Regression By Cleveland DataBase" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-3, April 2018, pp.1467-1470, URL: https://www.ijtsrd.com/papers/ijtsrd11402.pdf

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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 logistic regression on the Cleveland Heart Disease Database in order to present an accurate model of predicting heart disease.

Keywords :
heart disease prediction, logistic regression, Cleveland heart disease data base

Publication Details:

Unique Identification Number : IJTSRD11402

Published In : Volume-2 | Issue-3, April 2018

Page Number(s) : 1467-1470

Publisher Name : IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470

Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

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