Comparative study on heart disease prediction models using machine learning

Authors

  • Abhishek Sarda

Abstract

Deaths occurring due to heart diseases have been extremely high in the recent years. These
deaths take place irrespective of gender although the ratio between male and female that appear might
be skewed depending on the region that is in consideration. Heart disease is a problem that can start to
occur at a very early age also but mostly it happens at the age of 60 to 70. Now the challenge that we are
faced with here is the detection of the heart diseases at times can be a little tricky and is extremely
expensive in the present paradigm. Throughout the course of this paper we are going to do a
comparative study with regards to multiple machine learning algorithms like K-Nearest neighbour
(KNN), Random Forests (RF) and Logistic Regression. Our goal here is to detect he accuracies of these
respective algorithms and suggest the most optimal model.

Published

2020-11-01

Issue

Section

Articles