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?