Ensemble Machine Learning Algorithms for Predicting Cardiovascular Disease

Cardiovascular disease has evolved into one of the most dangerous diseases affecting human life. During the recent decade, it has emerged as one of the top causes of death among individuals all over the world. A correct identification of heart disease on time is more helpful for preventing the patients from high risk. Interpreting the complex interactions in medical data is difficult for medical practitioners. Machine learning algorithms extensively utilized for extremely beneficial in accurately diagnosing cardiac disease in a short period of time. The main objective of this paper is to introduce several heart disease prediction models utilizing an ensemble of machine learning algorithms to identify the best characteristics and also compared the performance of ensemble machine learning methods based on classification and regression models.