Project Scenario
A data analyst is researching risk factors for heart disease at a university hospital. There is access to a large set of historical data that can be used to analyze patterns between different health indicators (e.g. fasting blood sugar, maximum heart rate, etc.) and the presence of heart disease. Different logistic regression models were created to predict whether or not a person is at risk for heart disease. This could be used to evaluate medical records and look for risks that might not be obvious to human doctors. A classification random forest model was created to predict the risk of heart disease and a regression random forest model to predict the maximum heart rate achieved.