Predicting Heart Diseases through Feature Selection and Ensemble Classifiers

Abstract

Heart diseases or Cardiovascular Diseases are the leading cause of death globally. Amid the Covid-19 pandemic, the toll has further increased and is prevalent among all age groups. The reasons are associated with various side effects of lockdown or socio-economic affairs. It becomes extremely important to strengthen our research on diagnosis systems to timely and accurately identify the disease. This paper is an attempt to predict a healthy or heart patient using ensemble machine learning methods depending on selected features. The proposed model shows that after performing feature selection the ensemble models give optimum accuracy with significantly lesser features.