Assume the same information for TelMark as in Exercise 11-24. A member of the data science team points out that overfitting is often an issue

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Assume the same information for TelMark as in Exercise 11-24. A member of the data science team points out that overfitting is often an issue with decision trees. To avoid this issue, he suggests pruning the tree at depth 3 so that the third cut is not made.

Data from Exercise 11-24:

TelMark Mobile Services provides mobile phone services to millions of customers in the U.S. TelMark’s customer base is constantly changing as old customers leave the service and new customers join. This is called churn and it is a very important dynamic for the company to manage effectively because it has significant profit implications. Churn has increased recently, so managers at TelMark have started a program to offer targeted promotions to customers who are likely to abandon the service. They would like to develop a machine learning model to help identify these customers. Sylvia Restler is the management accountant assigned to work on the project with the data science team. Sylvia speaks with a few members of the customer service team to better understand why customers leave their platform. The team tells her that two variables are highly related to customer churn: number of lines per customer family plan and number of months the customer has been with the company. According to their data, customers who have already been with the company for a long time tend to stay, as do customers with many lines on their family plan. Sylvia asks the data science team to use these variables to create a decision tree.

The team uses the following as a validation set:

Required:
1. Using the pruned tree, classify each customer in the validation sample as leave or stay (if the probability of leave is greater than 0.5, classify the customer as leave). Calculate the proportion of customers correctly classified as in Exhibit 11-13, column 6.

Data from Exhibit 11-3:

2. Based on your answer to requirement 1 of this problem and Exercise 11-24, requirement 2, which tree should Sylvia use to identify customers who are likely to leave?
3. As the management accountant, what business recommendations could Sylvia make to management based on the decision tree model?

Depth 1 Depth 2 Depth 3 Leave 5 1 Leave