Question

A University is applying Classification methods in order to ldentity alumini 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 20 Donation No Donation 5375 23,439 The following table lists some information on individual observations from the validation set: Probability of Predicted Observation ID Actual Class Donation Class Donation 0.8 Donation No Donation No Donation No Donation Donation 0.1 0.6 (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? If required, round your answers to one decimal place. Do not round intermediate calculations. X. It is greater than 0.5, so The probability of Donation for Observation A is Observation A is classified as Donation by the random forest. ®. It is lesser than 0.5, so The probability of Donation for Observation B is Observation B is classified as No Donation by the random forest. X. It is greater than 0.5, so The probability of Donation for Observation C is Observation C is classified as Donation by the random forest. (b) Compute the values of accuracy, sensitivity, specificity, and precision. Explain why accuracy is a misleading measure to consider

Answer 1

Answer:-

Given That:-

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.

From the given data:

	Predicted
Actual	Donation	No-Donation
Donation	268 (TP)	20 (FN)
No-Donation	5375 (FP)	23,439 (TN)

a. Explain how the probability of Donation was computed for the 3 observations. Why were observations A and C classified as Donation and observation B was classified as No Donation?

The probability of Donation for observation A is 0.8. It is greater than 0.5, So observations A is classified as donation by the random forest.

The probability of Donation for observation B is 0.1. It is less than 0.5, So observation B is classified as No Donation by the random forest.

The probability of Donation for observation C is 0.6. It is greater than 0.5, So observation C is classified as Donation by the random forest.

b. Compute the values of accuracy, sensitivity, specificity, and precision. Explain why accuracy is a misleading measure to consider in this case.

$Accuracy=\frac{TP+TN}{Total \, \, rbs}$

= (268+23439)/29102

= 0.81

Accuracy is best measure to use, because less than  $\frac{288}{29102}\times 100$% = 1% of almuni is data have donated.

Sensitivity :-

268 TP + FN268 + 20

= 0.93

Specificity:-

$\frac{TN}{TN+FP}=\frac{23439}{23439+5375}$

= 0.81

Precision:-

$\frac{TP}{TP+FP}=\frac{268}{268+5375}$

= 0.0475

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