Heart Disease Prediction using Machine Learning Algorithms

Now-a-days, heart disease has the greatest impact in the cause of mortality. Although people's lives can be saved through accurate prediction of heart disease, it may also lead to death if the prediction is inaccurate. Heart disease prediction at an earlier stage is a very difficult task. The earlier prediction provides information about the patient's heart condition so that treatment can be made effectively. To solve problems which are complex and nonlinear, machine learning (ML) algorithms can be used. In order to enhance the accuracy of classification and prediction, different machine learning (ML) algorithms can be utilized together (ensemble models). K-Nearest Neighbor, Random Forest, Decision Tree are the various ML techniques that have been employed for ensemble models. The majority voting technique is utilized by the ensemble model for the prediction.