Identify all the strong association rules

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Reference no: EM133115718

Data Mining for Business Analytics and Cyber Security

Exercise

Question 1.
a) Calculate the confidence of rules A → BCD, and ABC → D given their support?
b) Given a frequent itemset (ABCD), generate all the association rules with three items on LHS (Body) and one item on RHS (Head)?
Please note: Rule form: X (LHS or Body) → Y (RHS or Head)
LHS stands for Left hand side and RHS stands for Right hand side in the rule.

Question 2.
Consider an example of a supermarket database which might have several thousand items of which 1000 items are frequent and several million transactions. Which part of the Apriori algorithm will be most expensive to compute? Why?

Question 3.
Consider the market basket transactions shown in the following table. Assume that min_support = 40% and min_confidence = 70%. Further, assume that the Apriori algorithm is used to discover strong association rules among transaction items.

705_Data Mining for Business Analytics2.jpg

a) Show step by step the generated Candidate itemsets (Ck) and the qualified frequent itemsets (Lk) until the largest frequent itemsets are generated.

b) Generate all possible association rules from the frequent itemsets obtained in the previous question. Calculate the confidence of each rule and identify all the strong association rules.

Reference no: EM133115718

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