The database Bank Marketing.xlsx** contains information on the results of a direct marketing campaign by a Portuguese bank. The purpose of the campaign was to enroll customers in a bank term deposit account. The data include demographic information (e.g., marital status) as well as financial information (e.g., size of balance). The goal is to create a Naïve Bayes model to determine which customers will enroll.

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).