is a management accountant at Keebler minus Olson , where he is in charge of their investment portfolio. James worked with a data scientist to develop a model that predicts how a given loan will perform in the future based on the characteristics of the borrower available on the peer-to-peer lending platform Mandel Credit. James Silva and the data scientist on his team work together to develop the following decision tree:

Requirement 1. Prune the tree at depth 3. Using the pruned tree, classify each loan in the validation sample as repay or default (if the probability of default is greater than 0.5 classify the loan as default). Calculate the proportion of loans correctly classified.

Start by classifying each loan in the validation sample as (0) Repay or (1) Default using the pruned tree.

ObservationIncomeCredit ScoreActual OutcomeModel Prediction (Pruned Tree)(1)(2)(3)(4)(5)1$85,000710(0) Repay 2$62,000650(1) Default 3$72,000660(0) Repay 4$75,000640(0) Repay 5$71,000680(0) Repay 6$59,000705(0) Repay 7$48,000690(1) Default 8$57,000685(0) Repay