1. Suppose that we have a sample data for four people and the data has four attributes. The data is given in the following table.

Name	Test-1 (nominal)	Test-2 (nominal)	Test-3 (nominal)
Jack	Code A	M	S
Joe	Code B	M	Y
Jimmy	Code C	N	M
Jill	Code A	F	Y
Jin	Code B	F	M

Use the three nominal attributes to calculate the distance between Joe and Jill.

2. A database has four transactions, given below,

TID	Date	items_bought
T10	1/10/2021	{K, A, D, B}
T20	1/11/2021	{D, A, C, E, B}
T30	2/1/2021	{C, A, B, E}
T40	2/3/2021	{B, A, D}

Assuming a minimum level of support min_sup = 60% and a minimum level of confidence min_conf = 80%.

(a) Find all frequent itemsets (not just the ones with the maximum width/length) using the Apriori algorithm. Show your workjust showing the final answer is not acceptable. For each iteration show the candidate (Ci) and acceptable frequent itemsets (Li).

(b) List all of the strong association rules, along with their support and confidence values.

3. Given a data cube summarizing the sales data of ABC company having three dimensions: address (with city values), time (with quarter values), and item (with item types), an analyst can roll up on sales data summarized by the city to see data summarized by country.

True

False