Loan Purpose Checking Savings Months Customer Months Employed Credit Risk New Car 396 228 13 26 Low Furniture 652 732 49 4 High Used Car 2484 0 49 46 Low Small Appliance 3565 0 31 32 Low Small Appliance 0 490 5 41 Low Small Appliance 16935 189 37 60 Low Small Appliance 0 763 13 46 Low Education 1257 0 10 65 Low New Car 0 637 13 21 High Furniture 457 318 19 108 Low New Car 0 116 49 45 High Small Appliance 6851 901 13 21 Low Small Appliance 829 583 7 18 Low Small Appliance 893 0 16 94 Low Business 12760 4873 13 73 Low Small Appliance 0 4449 25 87 High Furniture 0 836 25 99 Low Small Appliance 317 10980 13 17 High Business 0 265 13 10 Low Small Appliance 0 762 10 1 High Used Car 105 320 28 54 Low Small Appliance 0 18716 19 93 Low Small Appliance 0 3273 13 4 High Small Appliance 0 6490 19 85 Low Furniture 617 411 31 3 Low Furniture 0 463 11 13 High Furniture 0 180 5 2 Low Small Appliance 0 364 5 35 Low New Car 497 888 16 3 High New Car 682 2017 37 85 High Business 0 500 25 1 High Furniture 0 836 16 4 Low Business 0 11481 25 18 High Business 0 3285 7 21 Low Used Car 219 841 43 0 Low New Car 1613 0 25 118 Low Education 977 463 10 61 High Education 197 0 37 17 Low Small Appliance 0 813 43 28 High New Car 0 102 7 0 Low Business 177 0 49 9 Low Education 705 0 25 24 Low Small Appliance 651 0 37 102 Low New Car 0 272 7 90 High New Car 122 460 37 109 High Used Car 819 0 13 23 Low Large Appliance 0 15800 16 40 Low Furniture 0 815 19 13 High New Car 789 989 31 0 High Furniture 0 0 31 53 High

Use the given data to classify the record below using the k-NN algorithm for k=1 to 5 . 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. (Kunm to rour veciral praces as meeued.)