Heart Disease Analysis Using Machine Learning Techniques

Abstract

One of the most common problem these days is heart disease, which can be quite severe in old ages and also in people who don’t live a healthy lifestyle. It can be prevented to an extent if people maintain a decent eating habit and go for a regular check-up. Deaths due to heart disease has become a major issue, approximately each minute a person dies due to heart disease, if we take a look at both male and female category then we find out that this ratio varies accordingly to the region also this ratio is considered for the people of age group 25–69. People get caught with such disease at an early age without knowing it, hence it has become a challenge to predict the cause of this disease. There are various algorithms which helps in data analysis by using different combination of algorithms. In this paper, A comparative study has been done using the different kind of machine learning algorithms like Support Vector Machine (SVM), Linear Regression, Decision Tree, Random Forest, data models for prediction would also be used that could tell whether the patient is having a heart disease or not.