Please answer 1, 2 and 3 number questions with proper explanation

A bank is interested in identifying different attributes of its customers, and below is the sample data of 150 customers. In the data table for the dummy variable Gender, 0 represents Male and 1 represents Female.And for the dummy variable Personal loan, 0 represents a customer who has not taken a personal loan and 1 represents a customer who has taken a personal loan.

Partition the data into training (50 percent), validation (30 percent), and test (20 percent) sets. Classify the data using k-nearest neighbors with up to k = 10. Use Age, Gender, Work experience, Income (in $1000s), and Family size as input variables and Personal loan as the output variable. Be sure to Normalize input data and to Score on best k between 1 and specified value. Generate lift charts for both the validation data and test data.

1. For the cutoff probability value 0.5, what value of k minimizes the overall error rate on the validation data? Explain the difference in the overall error rate on the training, validation, and test data.
2. Examine the decile-wise lift chart on the test data. Identify and interpret the first decile lift.
3. For cutoff probability values of 0.5, 0.4, 0.3, and 0.2, what are the corresponding Class 1 error rates and Class 0 error rates on the validation data?

Age	Gender	Work experience	Income (in $1000s)	Family size	Personal loan
47	0	22	53	3	1
26	1	3	22	1	1
38	0	16	29	4	1
37	0	12	32	6	1
44	0	22	32	3	0
55	1	30	45	7	0
44	1	23	50	2	0
30	1	5	22	2	0
63	0	35	56	2	0
34	1	8	23	4	0
52	0	26	29	1	1
55	0	25	34	2	1
52	0	28	45	3	1
63	1	29	23	3	1
51	1	30	32	4	0
41	0	18	21	5	1
37	0	14	43	4	1
46	0	23	23	3	1
30	1	6	18	3	1
48	1	25	34	2	0
50	1	22	21	1	1
56	0	31	24	4	0
35	1	9	23	3	1
39	0	13	29	5	1
48	0	22	34	6	0
51	1	21	39	2	1
27	1	3	26	1	1
57	1	32	49	2	1
33	1	12	39	3	1
58	0	33	32	2	0
46	0	21	45	3	1
32	0	6	23	5	0
56	1	28	45	3	1
35	1	12	28	4	1
47	1	23	38	1	1
50	0	23	32	3	0
57	1	25	32	4	1
38	0	15	25	5	1
52	1	24	22	2	1
56	0	31	19	3	1
47	1	24	34	4	0
54	0	31	45	2	1
25	0	2	21	1	1
40	1	16	34	6	0
61	1	30	49	2	1
29	1	6	34	1	1
52	0	25	39	3	1
56	0	31	54	2	1
61	0	33	43	2	0
26	0	4	23	2	1
60	1	30	56	3	0
37	1	12	23	5	0
39	1	14	39	4	0
46	1	21	34	5	0
59	1	30	39	2	0
54	0	31	28	1	1
27	0	4	22	1	1
54	0	30	45	2	0
42	1	18	36	4	0
64	0	35	46	2	0
33	1	8	32	6	1
65	0	34	36	1	0
38	0	13	32	4	0
48	1	23	26	5	0
31	1	7	32	3	0
39	0	15	35	5	1
58	1	28	45	2	0
51	0	26	23	3	0
41	0	18	34	3	0
36	1	12	32	2	0
39	0	12	22	4	0
58	0	29	34	2	0
42	1	15	45	1	0
44	1	21	32	3	0
65	1	35	54	2	0
40	0	13	23	5	0
33	1	11	41	4	0
45	1	24	29	5	0
38	0	12	24	4	1
32	1	10	28	3	1
51	0	30	43	2	1
32	0	11	34	1	1
46	0	22	39	4	1
44	1	21	25	3	0
41	1	15	28	2	1
54	1	29	54	4	1
26	1	3	24	2	0
33	0	8	26	3	1
45	1	20	34	4	0
63	1	30	54	2	0
55	0	31	49	3	1
49	1	25	34	5	1
64	1	35	54	2	0
26	0	3	19	1	0
42	1	19	23	1	1
48	1	22	43	3	1
64	1	34	45	2	0
52	0	28	32	4	0
41	0	16	34	3	1
40	0	14	34	5	0
40	0	16	26	4	0
55	1	32	37	2	1
49	0	27	39	3	0
46	0	21	29	1	0
59	1	32	56	2	0
51	0	26	23	3	1
45	0	23	43	4	1
39	1	17	26	4	1
55	1	32	37	5	1
63	0	35	43	2	0
53	1	27	24	1	1
39	0	16	43	6	1
50	1	25	56	3	0
27	0	4	32	1	1
29	0	6	23	2	1
61	0	30	45	1	0
57	1	27	34	2	1
56	1	34	54	4	0
35	1	6	45	5	0
25	0	3	32	2	1
57	0	27	36	2	0
47	0	25	54	4	1
60	1	35	33	3	0
32	0	8	45	2	1
27	1	4	32	1	0
39	0	18	39	4	1
26	0	1	22	1	0
46	1	25	34	5	0
28	0	4	23	2	0
64	0	37	43	4	0
65	1	33	49	2	0
47	1	25	37	4	0
27	1	5	28	2	1
25	0	3	34	1	1
25	0	2	24	1	1
64	0	30	53	2	0
44	1	21	48	5	1
65	0	25	47	2	0
54	0	31	55	1	1
51	0	26	43	3	0
51	0	21	46	1	1
28	1	4	25	2	1
56	1	32	55	3	1
57	1	26	49	2	1
35	1	9	27	6	1
47	1	21	54	4	1
54	1	27	45	2	0
28	1	5	29	3	1
45	0	22	45	5	0
43	1	18	43	2	1