A university is applying classification methods in order to identify alumni who may be interested in donating money. The university has a database of 58,205 alumni profiles containing numerous variables. Of these 58,205 alumni, only 576 have donated in the past. The university has oversampled the data and trained a random forest of 100 classification trees. For a cutoff value of 0.5, the following confusion matrix summarizes the performance of the random forest on a validation set: Predicted Actual Donation No Donation Donation 268 20 No Donation 5,375 23,439 The following table lists some information on individual observations from the validation set: Observation ID Actual Class Probability of Donation Predicted Class A Donation 0.8 Donation B No Donation 0.1 No Donation C No Donation 0.6 Donation a. (10 points) Why were observations A and C classified as Donation and observation B was classified as No Donation? b. (20 points) Compute the values of accuracy, sensitivity, specificity, and precision. Explain why accuracy is a misleading measure to consider in this case