The database ICU Data.xlsx contains information on 200 subjects from a much larger study of the survival of patients admitted to an intensive care unit (ICU) of a hospital. The data provided include basic demographic information (e.g., age and sex) as well as detailed medical data (e.g., blood gas measurements). The goal is to create a Logistic Regression model to determine which patients admitted to the ICU will live.

In each of the following exercises, the goal is to develop a classification or prediction model for the given situation and data. Follow these steps:

1. Examine the data descriptions and explore the data.
2. Clean the data as needed.
3. Transform the data as needed (e.g., create dummy variables for categorical variables).
4. Partition the data.
5. Run the specified algorithm.
6. Interpret the results and choose the best model (e.g., choose the best k in the k-Nearest Neighbor method).