Use the given data to classify the record below using the k-NN algorithm for

k=1 to 5

Loan Purpose Checking Savings Months Customer Months Employed Repairs 0 900 25 4

Loan Purpose Checking Savings Months Customer Months Employed Credit Risk Small Appliance 0 739 13 12 Low Small Appliance 6509 493 37 9 High New Car 0 3305 11 15 Low New Car 0 821 25 63 High Furniture 652 732 49 4 High Business 141 245 22 33 Low Small Appliance 265 947 25 5 High New Car 0 659 19 5 High New Car 580 0 11 8 High New Car 0 1366 19 17 Low Business 758 2665 13 31 Low New Car 166 922 13 2 High Small Appliance 5133 698 19 14 High New Car 0 116 49 45 High Furniture 13496 650 19 20 High Used Car 0 609 37 6 Low Small Appliance 0 10853 25 81 Low New Car 0 466 25 42 High Used Car 0 270 25 25 Low Furniture 0 909 25 3 Low Furniture 0 948 19 2 Low Used Car 0 309 49 37 Low Used Car 105 320 28 54 Low Furniture 468 14186 22 24 Low Education 522 385 10 66 Low Small Appliance 895 243 13 4 High New Car 0 771 25 0 High Business 8948 110 31 90 High Small Appliance 0 208 13 23 Low Repairs 0 718 19 0 High Used Car 0 999 25 0 Low New Car 682 2017 37 85 High Used Car 0 859 31 89 Low Small Appliance 0 1218 13 38 Low Furniture 0 8944 25 66 Low Education 0 403 7 5 Low Small Appliance 256 954 10 13 Low New Car 0 207 13 119 High New Car 0 483 19 90 High New Car 0 102 7 0 Low Used Car 271 7090 25 2 High Furniture 0 12721 37 31 Low Small Appliance 17366 0 16 21 High Small Appliance 242 0 19 6 Low New Car 0 862 49 62 High Furniture 0 435 19 16 High Furniture 0 369 7 23 Low Furniture 0 815 19 13 High Small Appliance 765 10406 10 24 Low Used Car 0 276 25 91 Low

Complete the table below for the nearest neighbors and for the classification of the new record for each value of k.

k	Distance	Classification
1	nothing	Low Tie High
2	nothing	Low High Tie
3	nothing	Low Tie High
4	nothing	High Tie Low
5	nothing