Consider the following data concerning credit default:

Age	Loan	Default	D1	D2
25	40 000	N	102 000	104
35	60 000	N	82 000	69
45	80 000	N	62 000	92
20	20 000	N	122 000	28
35	120 000	N	22 000	125
52	18 000	N	124 000	55
23	95 000	Y	47 000	98
40	62 000	Y	80 000	74
60	100 000	Y	42 000	117
48	220 000	Y	78 000	225
33	150 000	Y	8 000	154

Age and Loan are two numerical variables (predictors) and Default is the target.

Use the k-NN algorithm with k=3 and the given training set to classify an unknown case (Age=48 and Loan=142 000) using Euclidean distance, and without Normalisation for the following cases:

1. Use the loan amount as is and
2. Use the loan amount in 1000 units.

You are also required to comment on your result.

The calculation for both part (i) and (ii) are included in the data table: columns D1 and D2