QUESTION 26

CUSTOMER ID	AGE	EXPERIENCE	INCOME	FAMILY MEMBERS	EDUCATION LEVEL	CLASS
1	25	1	49000	4	UNDERGRADUTE	BAD
2	45	19	34000	3	UNDERGRADUTE	GOOD
3	39	15	11000	1	UNDERGRADUTE	BAD
4	35	9	100000	1	GRADUTE	GOOD
5	35	8	45000	4	GRADUTE	BAD
6	53	27	72000	2	GRADUTE	GOOD
7	50	24	22000	1	GRADUTE	BAD
NEW CUSTOMER	34	9	33000	1	GRADUATE	?

if we would like to use k-nn model (k=5) to make prediction for the the new customer's group, how can we do that?

Describe the process of your prediction including the distance calculation. (To make the problem simplified, no need to consider normalization)

Note: You need to actually do the calculations of distances and based on the calculation result, talk about whether the new customer should be GOOD/ BAD

For grading:

The calculation of Euclidean distances -6 points

The description of the process (after calculate the Euclidean distances, how the model should make a prediction) - 5 points