Question

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 268 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 Predicted Class Donation A Donation 0.8 Donation B No Donation 0.1 No Donation C No Donation 0.6 Donation a) Compute the values of accuracy, sensitivity, specificity, and precision.
b) Explain how the probability of Donation was computed for the three observations. Why were Observations A and C class fled as Donation and Observation Donation?

Answer 1

The accuracy in the research done by university is 0.81, sensitivity is 0.93, specificity is 0.81 and precision is 0.047.

Given sample size of 58205 and proportion of people donated 576. Cutoff is 0.5.

Probability is the chance of happening an event among all the events possible. It lies between 0 and 1.

TP=total people donated in sample, TN=total number of people,FP=donation,FN=No donation

Accuracy is calculated as under:

=(TP+TN)/(TP+TN+FP+FN)

=(268+23439)/(238+23439+5375+20)

=23707/29102

=0.81

Accuracy=0.81

Sensitivity is calculated as under:

=TP/(TP+FN)

=268/(268+20)

=268/288

=0.93

Precision is calculated as under:

=TP/(TP+FP)

=268/(268+5375)

=268/5643

=0.047

Their values are the probabilities in itself.

Hence accuracy is 0.81, sensitivity is 0.93, specificity is 0.81 and precision is 0.047.

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