1. Vary the value of k from 1 through 10. Based on the continuous (kNN regression)

prediction error measures, what is the optimal number of nearest neighbors employ?

a. 1

b. 2

c. 3

d. 4

e. 5

f. 6

g. 7

h. 8

i. 9

j. 10/n2. Based on the confusion matrix you observe when k = 5, calculate the prediction accuracy of

the KNN classifier in cell B30 (Hint: overall accuracy is the proportion of the 20 predictions that

were correct, i.e., on the diagonal of the confusion matrix).

a) 65%

b) 35%

c) 40%

d) We cannot answer this question without more information./n3.Vary the value of k from 1 through 9. Considering the discrete, KNN classifier's prediction

accuracy, what is the optimal number of nearest neighbors employ, i.e., what value of k

maximizes the prediction accuracy?

a. 1

b. 2

c. 3

d. 4

e. 5

f.

6

60

h.

i.

7

8

9/n4. Yes, or no? Would either of these kNN predictive models be useful for generating

recommendations related to a new song that has just been released, i.e., which has not yet

been rated by any users, or for a new user, i.e., a user who has not yet entered any song ratings?

(Hint: you can assume that you would have details on the new user or the new song).

a. YES

b. NO