Use set.seed$(6751342)$ and split the credit card default data set into training and validation sets using $70\%$ and $30\%$ split, respectively. How many rows are in the original data set, the training set, and the validation set?

Use set.seed$(6751342)$ and create a classification decision tree for the default variable using missed payment, credit utilization, and assets as predictors. Include the cost$-$complexity $($cp$)$ table.

Plot the validation error against the cost$-$complexity parameter $($cp$).$ What is an appropriate cp value to use in pruning the tree?

Use set.seed$(6751342)$ and prune the tree using the appropriate cp value and include the plot of the resulting decision tree. IN R