Which appear to be the three or four most important car specifications for predicting the car's price? Compare the prediction errors of the training, validation, and test sets by examining their RMS error and by plotting the three boxplots. What is happening with the training set predictions? How does the predictive performance of the test set compare to the other two? Why does this occur? How might we achieve better validation predictive performance at the expense of training performance? Create a best pruned tree using the same data partitioning. Compared to the deeper tree, what is the predictive performance on the validation set? and on the training set?