Applying Zhang's rule

In Chapter 2, we learned that Zhang's rule is a continuous measure of association between two items that takes values in the [-1,+1] interval. A -1 value indicates a perfectly negative association and a +1 value indicates a perfectly positive association. In this exercise, you'll determine whether Zhang's rule can be used to refine a set of rules a gift store is currently using to promote products.

Note that the frequent itemsets have been computed for you and are available as frequent_itemsets. Additionally, zhangs_rule() has been defined and association_rules() have been imported from mlxtend. You will start by re-computing the original set of rules. After that, you will apply Zhang's metric to select only those rules with a high and positive association.

Generate the set of association rules with a lift value of at least 1.00.
Set the antecedent support threshold to 0.005.
Compute Zhang's rule and assign the output to the column zhang in rules.
Select the rules that have a Zhang's metric that is greater than 0.98.

Exercise

Applying Zhang's rule

Instructions