Apriori algorithm. We are given the following transactions

Apriority algorithm. We are given the following transactions a. How many unique possible itemsets can you come up with using just the above transactions? b. How many association rules can you make using {X1, X2, X3}? An association rule should contain all the items i.e. X1, X2 and X3. c. What is the support for the following itemsets (i) {X1, X2}, (ii) {X3, X1} d. What is the confidence for (i) {X1, X2} rightarrow {X3}, (ii) {X3} rightarrow {X1, X2} e. In the apriori algorithm, if our minsup = 0.5, can we prune the item set {X4, X2, X3}. Briefly explain. f. If our minconf = 0.5, for the itemset {X1, X2, X3}, can we prune the rule X2 rightarrow X1, X3. Briefly explain. g. Do you think, as the minsup value is increased, the apriority algorithm becomes faster or slower. Briefly explain. h. In general, suppose we know that the support for an itemset is S, then can we say that the confidence for any rule generated from that itemset is less than or equal to S