1. Consider a dataset for frequent set mining as in the following table where we have 6 binary features and each row represents a transaction. TID Items 1 {c, e} 2 {b, c, d, f} 3 {a, e} 4 {a, b, c, f} 5 {d} 6 {a, d, f} 7 {c, d, e, f} 8 {a, b, e} 9 {a, d} 10 {b, c, f} a. Illustrate the first three passes of the Apriori algorithm (set sizes 1, 2 and 3) for support threshold of 3 transactions. For each stage, list the candidate sets Ck and the frequent sets Lk. What are the maximal frequent sets discovered in the first 3 levels? b. Pick one of the maximal sets that has more than 1 item, and check if any of its subsets are association rules with support (i.e. frequency) at least 0.3 and confidence at least 0.6. Please explain your answer and show your work