TID Items 100 2. 3. 4. 5, 6. 8 200 1, 2, 3. 5, 6 300 1, 4. 5. 7, 8 400 2. 3. 4. 5, 6 500 1, 2, 3, 4, 5, 7 600 1, 3. 8 (1) Mine all frequent itemsets using the Apriori algorithm, which we discussed in the class, with the minimum support = 50% (or 3 or more transactions). Show all candidate itemsets and frequent itemsets. You should follow the process described in the book and lecture (i.e., C1 - L1 - C2 - L2 - ...). You don't need to show pruning steps. To save your time, Ll is given below: L1: Itemset 2 4 Count 4 4 5 4 5 (2) Sort all frequent 4-itemsets by their item number. Then, select the first frequent 4-itemset form the sorted list of frequent 4-itemsets and mine all strong rules from this itemset that have the format {W. X} => {Y, Z), where W. X. Y, and Z are individual items. Assume that minimum confidence = 80%