Heart Disease Classification Using Machine Learning Algorithms

Abstract

Heart illness, or cardiovascular disease, is one of the main medical concerns at the moment. The purpose of my research, " Heart Disease classification using Machine learning Algorithms" is to draw attention to the risk factors for heart disease. To reach the maximum accuracy in heart disease prediction, I analyze numerous patient variables using multiple algorithms. Logistic Regression, K-Nearest Neighbours Classifier, Support Vector machine, Decision Tree Classifier, Random Forest Classifier, XGBoost Classifier are some of the algorithms that were used. With an accuracy of 97.99%, the Random Forest Classifier was the most accurate of them. People are able to make well-informed judgments about their next actions for more successful therapy because of this high predictive accuracy.