JETIREXPLORE- Search Thousands of research papers



Published in:

Volume 7 Issue 7
July-2020
eISSN: 2349-5162

Unique Identifier

JETIR2007127

Page Number

1027-1031

Share This Article


Title

Ameliorate Performance of Predicting Diseases Related to Heart by Utilizing ML Techniques

ISSN

2349-5162

Cite This Article

"Ameliorate Performance of Predicting Diseases Related to Heart by Utilizing ML Techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 7, page no.1027-1031, July-2020, Available :http://www.jetir.org/papers/JETIR2007127.pdf

Abstract

Background: Disease Prediction framework dependent on prescient displaying predicts the infection of the client based on the indications that client gives as a contribution to the framework. The framework examines the indications gave by the client as info and gives the likelihood of the ailment as a yield. Ailment Prediction is finished by actualizing 5 systems, for example, Naïve Bayes, KNN, Decision Tree, Linear Regression and Random Forest Algorithms. Aim: To study different ML algorithms to predict diseases related to heart through using considering various issues such as accuracy and precision. Results: Random Forest algorithm outperforms from all the algorithms with accuracy around 88%.

Key Words

Machine learning, Algorithms, Diseases related to Heart

Cite This Article

"Ameliorate Performance of Predicting Diseases Related to Heart by Utilizing ML Techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 7, page no. pp1027-1031, July-2020, Available at : http://www.jetir.org/papers/JETIR2007127.pdf

Publication Details

Published Paper ID: JETIR2007127
Registration ID: 235059
Published In: Volume 7 | Issue 7 | Year July-2020
DOI (Digital Object Identifier):
Page No: 1027-1031
ISSN Number: 2349-5162

Download Paper

Preview Article

Download Paper




Cite This Article

"Ameliorate Performance of Predicting Diseases Related to Heart by Utilizing ML Techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 7, page no. pp1027-1031, July-2020, Available at : http://www.jetir.org/papers/JETIR2007127.pdf




Preview This Article


Downlaod

Click here for Article Preview