Question

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

Answer 1

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.