In the previous video, we constructed two CART models. The first CART model, without the loss matrix, predicted bucket 1 for 78.6% of the observations in the test set. Did the second CART model, with the loss matrix, predict bucket 1 for more or fewer of the observations, and why?
Explanation
If you look at the classification matrix for the second CART model, we predicted bucket 1 less frequently. This is because, according to the penalty matrix, some of the worst types of errors are to predict bucket 1 when the actual cost bucket is higher.
