Random Forest Classifier based on Heart Disease Prediction

Abstract

In the medical field, the diagnosis of heart disease is the most difficult task. The diagnosis of heart
disease is difficult as a decision relied on grouping of large clinical and pathological data. Due to this
complication, the interest increased in a significant amount between the researchers and clinical
professionals about the efficient and accurate heart disease prediction. In case of heart disease, the
correct diagnosis in early stage is important as time is the especially important factor. Heart disease is
the principal source of deaths widespread, and the prediction of heart disease is significant at an
untimely phase. Machine learning in recent years has been the evolving, reliable, and supporting tools
in medical domain and has provided the greatest support for predicting disease with correct case of
training and testing.