In recent few decades, heart problems emerge as a deadly disease and becomes the major cause for death of large number of people around the world. It is one of the life-threating disease that needs to be diagnosed early with an accurate, feasible and reliable system. Traditional methods for proper treatment of heart disease in time is not enough. Developing a disease prediction system based on Machine Learning algorithm provides a reliable and more accurate disease diagnosis than traditional methods. So, this project implements machine learning algorithm to analyze their performances. In this project, a heart disease prediction system based on supervised learning algorithms: Random Forest (RF), Decision Tree (DT) and regression models: Linear Regression and Random Forest regression are implemented to get the best accuracy rate among all.
- Requirements
The provided code works in all python versions above 3.7.0.
- Installation
There are few libraries that need to be installed before running the codes.
- pip install -U scikit-learn
- pip install pandas
- pip install numpy