Problem #5 [12 points] There are 100,000 emails used to train a spam detection system - 5,000 of them are of spam and the rest are non-spam. To test the system, you have 10,000 emails 2,000 spam and 8,000 non-spam - in your test set. The results of the test are as follows: 250 of the spam emails are classified as non-spam, and the rest are classified as spam; 250 of the non-spam emails are classified as spam, and the rest are classified as non-spam. (a) Show the contingency table for this binary classification experiment. Label it clearly and fill out the table entries. (b) What is the false positive rate of the system in this experiment? (C) What is the false negative rate? (d) What is the error rate? (e) What is the precision? (f) What is the accuracy