Each dataset below contains 10 items and 10000 transactions. Dark cells indicate the presence of items, and white (and grey) cells indicate the absence of items. We will apply the Apriori algorithm to extract frequent itemsets with minsup = 20% (i.e., itemsets must contain at least 2000 transactions). (a) (b) (c) items items 2000 200 200 -4000 4000 4000 Transaction Transaction - 6000 6000 6000 800 8000 - 8000 10000 10000 - 10000 a) What is the number of frequent itemsets for each dataset? Which dataset will produce the greatest number of frequent itemsets? b) Which dataset will produce the longest frequent itemset? c) Which dataset will produce frequent itemsets with the highest maximum support? d) Which dataset will produce frequent itemsets containing items with widely varying support levels (i.e., itemsets containing items with mixed support, ranging from 20% to more than 70%)? e) What is the number of maximal frequent itemsets for each dataset? Which dataset will produce the greatest number of maximal frequent itemsets? f) What is the number of closed frequent itemsets for each dataset? Which dataset will produce the greatest number of closed frequent itemsets