Amelioratethe Accuracy rate of Heart disease Predictionusing Robust models of Machine Learning

In Present days after the COVID pandemic the heart diseases risks are growing throughout the world not only in the aged persons but also occurred in teenagers. It is very much needful requirement in the real world to predict the symptoms of heart diseases in advance before they attack the human body. Previously several researchers are trying to identify the heart disease occurred in human body in advance. In this process Machine learning algorithms are very much helpful to the researchers because those algorithms or models can be applied on the different data sets and observe the predicting accuracy in different dimensions. In this paper researcher used the SVM (Support Vector Machine), KNN (K nearest Neighbor) and Naive Bayes machine learning algorithms to improve the predicting accuracy of heart disease affected rate.