Question: Pruning a tree is important to ensure that the model has not overfit the data. Following the example provided in the book, prune the model

Pruning a tree is important to ensure that the model has not overfit the data. Following the example provided in the book, prune the model created in Question

3

to minimize

2

the cross

-

validation error. How did the tree change? How many levels does the pruned tree include? What are the

3

most important variables and their relative importance according to the pruned tree model?

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