Heart disease is easier to treat when it is detected in the early stages. Machine learning techniques may aid a more efficient analysis in the prediction of the disease.
Moreover, this prediction is one of the most central problems in medical, as it is one of the leading disease related to unhealthy lifestyle. So, an early prediction of this disease will be useful for a cure or averion.
In this study, we experiment with the heart disease dataset to explore the machine learning algorithms and build an optimum model to predict the disease.
We have used Decision Tree Algorithm for our predictions.