A Comparative Study on Prediction of Heart Disease and Classifiers Suitable Analysis

Abstract

Machine learning is a vital research area for today's computer scientists. Artificial Intelligence has a critical connection with ML-based research. The authors of this article used machine learning to determine whether a person has cardiac disease. Many people suffer from cardiovascular diseases (CVDs), which claim the lives of people all over the world. Machine learning may be used to determine whether a person has a cardiovascular illness by considering certain factors such as chest discomfort, cholesterol levels, age, and other factors. Classification algorithms based on supervised learning which is a type of machine learning can make diagnoses of cardiovascular diseases easy. People with heart disease are classified using algorithms such as K-Nearest Neighbor (KNN), Random Forest, Logistic Regression, Decision Tree Classifier, SVM, Naive Bayes, and Gradient Boosting Classifier. The K-Nearest Neighbor (K-NN) and Random Forest supervised machine learning techniques are employed in this paper thoroughly.