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Exercise

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.

Instructions

100 XP
  • 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.