For this lab, you will be using the .CSV files provided in the files_for_lab folder. These are cleaned versions of the learningSet data from the Case Study 'Healthcare for All'.
Begin a new Jupyter Notebook after Forking and Cloning this Repo.
- Apply the Random Forests algorithm but this time only by upscaling the data to deal with the imbalance.
- Use Feature Selections that you have learned in class to decide if you want to use all of the features (Variance Threshold, RFE, PCA, etc.)
- Re-run the Random Forest algorithm to determine if the Feature Selection has improved the results.
- Discuss the output and its impact in the business scenario. Is the cost of a false positive equals to the cost of the false negative? How would you change your algorithm or data in order to maximize the return of the business?