Abstract: Heart disease can be considered as one of the complex diseases and globally many people suffered from the
disease. In the recent years, a death because of heart disease has become a significant issue. So, it is necessary to design
a system that will correctly diagnose heart disease. In this paper, an efficient and accurate system to diagnose heart
disease is proposed and the system is based on Machine learning techniques resulting in improving the accuracy in the
prediction of heart disease. A cardiovascular dataset is classified by using several state of the art Machine Learning
algorithms that are precisely used for disease prediction. The prediction model is introduced with the several
classification techniques and the different combinations of features. We try to produce an enhanced performance with
high accuracy level through the prediction model for cardiovascular disease with the use of Machine Learning
techniques like Random Forest, Naïve Bayes and SVM.
Keywords- Machine learning, heart disease prediction, cardiovascular disease (CVD), feature selection, prediction model.