A) Suppose we train a model to predict whether an email is Spam or Not Spam. After training the model, we apply it to a test set of 200 new email messages (also labelled) and the model produces the contingency table below. (3 Marks) 1) Compute the precision of this model with respect to the "Spam" class and with respect to the "Not Spam" class. 2) Compute the recall of this model with respect to the "Spam" class and with respect to the "Not Spam" class. Predicted Class Spam Not Spam 60 0 120 20 True Class Spam Not Spam 3) Comment on the performance of the model B) When a model is said to be overfitting in regression? How to combat overfitting in that case? Exaplain. (2 Marks)