Consider the transaction database in the table below:
able[[Transaction ID,Items Bought],[0001,(a,d,d:)
Consider the transaction database in the table below:
able[[Transaction ID,Items Bought],[0001,(a,d,d:)
a) Compute the support for itemsets{a}{bc}and{a,b.c by treating each transaction ID as a market basket.You have 10 transactions b Use the results inpart(a to compute the confidencefor the association rules {b}{a}and{a}{bc} Using Apriori algorithm,generate frequent itemsets for min sup count -4You need to show the complete calculations including intermediate candidate itemsets Ci and Li where i is the level l2..etc. CP If you use the Brute-force approach to find all possible association rules,how many candidate itemsets exist for the given market basket? Explain your answer e How does the Apriori algorithm improve upon the brute-force algorithm? f) We generally will be more interested in association rules with a high confidence threshold.However,often we will not be interested in association rules that have a confidence of 100%Why?Explain your answer