Question

Use the K-NN algorithm to classify the new data in the excel file Credit Approval Decisions...

Use the K-NN algorithm to classify the new data in the excel file Credit Approval Decisions Coded using only credit score and years of credit history as input variables.

We're only allowed to use excel or analytic solver to answer problems. I don't know what python is.

 Homeowner Credit Score Years of Credit History Revolving Balance (\$) Revolving Utilization (%) Decision Y 592 3 21000 15 Reject N 653 8 4000 90 Reject Y 576 1 8500 25 Reject N 733 4 16300 70 Approve N 726 13 2500 90 Approve Y 675 14 16700 18 Approve

K nearest neighbors:

Find the euclidean distance between the new values and all of the old values.

Eg. If the new Credit Score = 633

Years of Credit History = 3

You have a set (633,3). This is (X2,Y2)

Euclidean distance = SQRT ((X1-X2)^2+ (Y1-Y2)^2)

So for row 1, Euclidean Distance = SQRT ((592-633)^2 + (3-3)^2) = 41

Look at the screenshot below:

This should be clear Let me know in case you have any questions.