se 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   Business 500 800 15 20   Loan Purpose Checking Savings Months Customer Months Employed Credit Risk Business 0 533 14 2 Low Repairs 207 0 28 116 Low Furniture 101 3871 13 5 High Furniture 0 485 37 23 High Business 141 245 22 33 Low Used Car 2484 0 49 46 Low Small Appliance 0 323 49 42 High Used Car 0 109 25 26 Low Furniture 4256 0 16 36 Low Business 870 917 28 6 High New Car 162 595 22 10 Low New Car 0 659 19 5 High New Car 0 1366 19 17 Low Small Appliance 0 552 25 4 High Repairs 0 626 43 0 Low Furniture 828 391 9 12 High Small Appliance 317 10980 13 17 High Education 0 922 37 9 High Repairs 216 262 37 2 High New Car 0 470 13 0 Low New Car 8176 12230 7 5 Low Furniture 468 14186 22 24 Low Small Appliance 0 18716 19 93 Low Used Car 0 14717 28 7 Low New Car 0 0 25 19 High New Car 585 2223 16 0 High New Car 5588 0 22 10 High New Car 0 605 37 20 High Small Appliance 895 243 13 4 High Business 8948 110 31 90 High Used Car 0 10099 16 108 Low New Car 0 9125 13 24 High Small Appliance 795 16804 49 40 High Education 977 463 10 61 High Furniture 8636 214 11 3 Low New Car 949 0 49 36 Low New Car 0 693 19 28 High New Car 0 648 15 57 High Used Car 271 7090 25 2 High Used Car 0 904 49 119 High Small Appliance 5960 129 13 16 Low Furniture 0 987 37 101 High Education 842 0 37 9 Low Repairs 3111 0 13 27 Low Small Appliance 0 302 10 30 High Small Appliance 17366 0 16 21 High Business 929 124 9 1 Low Small Appliance 0 17124 13 95 Low Used Car 2472 0 37 41 Low New Car 193 2684 13 5 High 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 enter your response here ▼     2 enter your response here ▼   High Low Tie 3 enter your response here ▼   Low High Tie 4 enter your response here ▼   Tie High Low 5 enter your response here ▼   High Low Tie ​(Round to four decimal places as​ needed.)

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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
 
Business
500
800
15
20

 

Loan Purpose

Checking

Savings

Months Customer

Months Employed

Credit Risk

Business

0

533

14

2

Low

Repairs

207

0

28

116

Low

Furniture

101

3871

13

5

High

Furniture

0

485

37

23

High

Business

141

245

22

33

Low

Used Car

2484

0

49

46

Low

Small Appliance

0

323

49

42

High

Used Car

0

109

25

26

Low

Furniture

4256

0

16

36

Low

Business

870

917

28

6

High

New Car

162

595

22

10

Low

New Car

0

659

19

5

High

New Car

0

1366

19

17

Low

Small Appliance

0

552

25

4

High

Repairs

0

626

43

0

Low

Furniture

828

391

9

12

High

Small Appliance

317

10980

13

17

High

Education

0

922

37

9

High

Repairs

216

262

37

2

High

New Car

0

470

13

0

Low

New Car

8176

12230

7

5

Low

Furniture

468

14186

22

24

Low

Small Appliance

0

18716

19

93

Low

Used Car

0

14717

28

7

Low

New Car

0

0

25

19

High

New Car

585

2223

16

0

High

New Car

5588

0

22

10

High

New Car

0

605

37

20

High

Small Appliance

895

243

13

4

High

Business

8948

110

31

90

High

Used Car

0

10099

16

108

Low

New Car

0

9125

13

24

High

Small Appliance

795

16804

49

40

High

Education

977

463

10

61

High

Furniture

8636

214

11

3

Low

New Car

949

0

49

36

Low

New Car

0

693

19

28

High

New Car

0

648

15

57

High

Used Car

271

7090

25

2

High

Used Car

0

904

49

119

High

Small Appliance

5960

129

13

16

Low

Furniture

0

987

37

101

High

Education

842

0

37

9

Low

Repairs

3111

0

13

27

Low

Small Appliance

0

302

10

30

High

Small Appliance

17366

0

16

21

High

Business

929

124

9

1

Low

Small Appliance

0

17124

13

95

Low

Used Car

2472

0

37

41

Low

New Car

193

2684

13

5

High

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
enter your response here
 
 
2
enter your response here
 
High
Low
Tie
3
enter your response here
 
Low
High
Tie
4
enter your response here
 
Tie
High
Low
5
enter your response here
 
High
Low
Tie
​(Round to four decimal places as​ needed.)
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