The purpose of this project is to predict whether a patient has heart disease or not, based on clinical and demographic variables. We used the Cleveland Heart Disease dataset and compared three models: a logistic regression, a cost-sensitive decision tree and a random forest. Our goal is to evaluate model performance and see which approach is most reliable for this classification task.

Construct a time series plot, find an accurate forecasts based on MSE