10 test points were classified using a 4-nearest neighbors algorithm. The actual y labels and the 4-NN classifications are summarized in the table below.

x1	x2	y+labels	predicted+y
4.8	6.2	0	1
5	1	0	0
1.7	2	1	1
7.6	4.3	0	0
7	5.1	1	1
4.2	9.8	1	1
2.2	9	1	1
4.6	8	1	1
9.7	6.4	0	0
9.2	5.9	0	1

a. Using the above information, need to fill out the confusion matrix below.

	Predicted Value
0	1
Actual	0
Value	1

b. What is the overall error rate for this 4-nearest neighbours algorithm?

Error Rate (%) = ?

c. What is the accuracy for this 4-nearest neighbours algorithm?

Accuracy (%) = ?