Exercise

# Generating association rules

In the final exercise of the previous section, you computed itemsets for the novelty gift store owner using the Apriori algorithm. You told the store owner that relaxing support from 0.005 to 0.003 increased the number of itemsets from 9 to 91. Relaxing it again to 0.001 increased the number to 429. Satisfied with the descriptive work you've done, the store manager asks you to identify some association rules from those two sets of frequent itemsets you computed.

Note that `pandas`

has been imported for you as `pd`

and the two frequent itemsets are available as `frequent_itemset_1`

and `frequent_itemset_2`

. Your objective is to determine what association rules can be mined from these itemsets.

Instructions

**100 XP**

- Import the algorithm from
`mlxtend`

that computes association rules from`apriori`

algorithm results. - Complete the statement to compute association rules for
`frequent_itemsets_1`

using the support metric and a threshold of 0.0015. - Complete the statement to compute association rules for
`frequent_itemsets_2`

using the support metric and a threshold of 0.0015.