In 2020, alumni collectively donated $11.37 billion to their colleges and universities, according to an annual report from the nonprofit Council for Aid to Education. That is an increase of 14.5 percent from the prior year, which the report attributes, at least in part, to a strong stock market.  Some colleges and universities have a particularly high percentage of former students who make financial contributions. In that period, the 10 institutions with the highest percentages of undergraduate alumni donors boasted an average giving rate of 51.5 percent. Alumni donor count is used to calculate alumni participation by dividing it by the number of living alumni on record. For example, if your institution has 100,000 alumni of record (i.e., living with a good address) and 20,000 of them made a gift last year, your alumni participation rate is 20%.  The importance of alumni participation cannot be understated; for example, U.S. News & World Report’s Best Colleges, the most prominent college ranking, weighs alumni donor participation in evaluating a school. University-X 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. In the past, of the 58,205 alumni 3,850 have donated. The university has sampled the data and trained a KNN classification algorithm with k=10. For a cutoff value of 0.5, the following confusion matrix summarizes the performance of the validation set:   Predicted Actual Donation No Donation Donation 2102 539 No Donation 4209 33017   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

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
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In 2020, alumni collectively donated $11.37 billion to their colleges and universities, according to an annual report from the nonprofit Council for Aid to Education. That is an increase of 14.5 percent from the prior year, which the report attributes, at least in part, to a strong stock market.  Some colleges and universities have a particularly high percentage of former students who make financial contributions. In that period, the 10 institutions with the highest percentages of undergraduate alumni donors boasted an average giving rate of 51.5 percent.

Alumni donor count is used to calculate alumni participation by dividing it by the number of living alumni on record. For example, if your institution has 100,000 alumni of record (i.e., living with a good address) and 20,000 of them made a gift last year, your alumni participation rate is 20%.  The importance of alumni participation cannot be understated; for example, U.S. News & World Report’s Best Colleges, the most prominent college ranking, weighs alumni donor participation in evaluating a school.

University-X 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. In the past, of the 58,205 alumni 3,850 have donated. The university has sampled the data and trained a KNN classification algorithm with k=10. For a cutoff value of 0.5, the following confusion matrix summarizes the performance of the validation set:

 

Predicted

Actual

Donation

No Donation

Donation

2102

539

No Donation

4209

33017

 

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

 

  1. Explain how the probability of Donation was computed for the 3 observations, and why were observations A and C classified as Donation and observation B was classified as No Donation.

 

  1. Evaluate the performance of the classifier. Provide a brief but formal report with your analysis. Include critical measures that can be derived from the confusion matrix, their interpretation and your overall recommendation as to the usefulness of the classifier.
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