Apply the Apriori algorithm to generate frequent itemsets and

association rules. Show your calculations for each step clearly.

Consider the following transaction dataset:

Transaction ID Items Purchased

T$1$ Milk, Bread, Butter

T$2$ Bread, Butter, Eggs

T$3$ Milk, Bread, Butter, Eggs

T$4$ Milk, Bread

T$5$ Milk, Eggs

$1.$ Generate Frequent Itemsets:

o Use the Apriori algorithm with a minimum support count of $2.$

o List all frequent $1-$itemsets, $2-$itemsets, and $3-$itemsets.

$2.$ Generate Association Rules:

o Using the frequent itemsets generated above, generate all association

rules with a minimum confidence of $60\%.$

o For each rule, calculate the support, confidence, and lift.

$3.$ Answer the following questions:

o Which item is most frequently purchased?

o Are there any strong associations $($confidence $>80\%)$ between items? If

yes, describe them.