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: 

The following table lists some information on individual observations from the validation set.

a. Explain how the Probability of Donation was computed for the three observations.
Why were Observations A and C classified as Donation and Observation B was classified as No Donation?

b. Compute the values of accuracy, sensitivity, specificity, and precision. Explain why accuracy is a misleading measure to consider in this case. Evaluate the performance of the random forest, particularly commenting on the precision measure.

Transcribed Image Text:

Actual Donation Donation 268 No Donation 5375 Predicted No Donation 20 23,439