Prediction of Heart Disease using Random Forest
Nagaraj M. Lutimath, Neha Sharma, B K Byregowda
Abstract
Random Forests are of the vital models in machine learning. They are comprehensive and effective classification paradigms in machine learning. The random forest recognizes the most important attributes of a given problem. The heart disorder is a cardiovascular disease, with a set of conditions affecting the heart. During heart disease there will be heart beat problems with congenital heart disorders and coronary artery defects. Coronary heart defect is a heart disease, which decreases the flow of blood to the heart. When the flow of blood decreases heart attack occurs. It is necessary to analyse the prediction of heart attack based on the symptoms. Available data set instances of the patients with heart defects symptoms is taken and analysed in this paper. Python language is utilized to prediction of the accuracy.