Use the given data to classify the record below using the k-NN algorithm for k = 1 to 5. Months Months Loan Purpose Checking Savings Customer Employed Retraining 644 2000 20 60 Click the icon to view the table of classified records. 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 2 3 4 5 (Round to four decimal places as ne Tie Low High A2 J& C F A B C D E F G . 1 Loan Purpose Checking Savings bnths Custor months Employeredit Riscan Purpose Checking 2 Furniture 0 485 37 23 High Business 8948 3 Small Appliance 16935 189 37 60 LOW Small Applia 0 4 Fumiture 664 537 31 33 High Large Applia 0 5 Small Appliance 0 138 7 119 Low Small Applia 6 Used Car 0 789 25 28 Low Fumiture 0 7 Education 0 0 37 114| High New Car 18408 8 New Car 0 1366 19 17 Low New Car 0 9 Business 758 2665 13 31 Low Other 852 10 New Car 0 0 22 9 High Education 0 11 Small Appliance 0 680 25 3 High Business 0 12 Used Car 0 104 37 25 High New Car 1613 13 Small Appliance 514 405 49 13 High New Car 0 14 Furniture 19155 131 25 24 Low New Car 0 15 New Car 939 496 19 56 High Small Applia 651 16 New Car 0 466 25 42 High Business 257 17 Business 12760 4873 13 73 Low Small Applia 0 18 Fumiture 0 836 25 99 Low Fumiture 0 19 Furniture 0 13 89 High Small Applia 2846 20 New Car 8176 12230 7 5 Low Business 929 21 Furniture 617 411 31 3 Low New Car 0 22 New Car 0 544 25 o High Small Applia 0 23 Furniture 835 0 19 42 High 0 Small Applia 24 Furniture 352 7525 13 4 Low Small Applia 296 25 Small Appliance 0 3529 14 O Low Used Car 0 26 New Car 0 912 7 39 Low Furniture 983 L Savings pnths Custonponths Employ Credit Risk 110 31 90 High 208 13 23 Low 1238 13 o High 956 25 4 High 636 22 41 Low 212 13 9 Low 9016 49 22 High 3613 61 83 High 403 7 5 Low 3285 7 21 Low 0 25 118 Low 343 19 22 Low 648 15 57 High 0 37 102 Low 460 49 75 High 798 25 42 High 538 25 59 High 0 13 14 Low 124 9 1 Low 862 49 62 High 519 31 23 Low 707 7 26 Low 818 19 93 Low 607 37 17 High 950 13 5 High 803 WS16