The associative rules method is an example of an unsupervised grouping method, that is, the goal is not used to direct how the grouping is generated. This method groups observations and attempts to understand links or associations between different attributes of the group. Associative rules have been applied in many situations, such as data mining retail transactions. This method generates rules from the groups, as the following example:
IF the customer's age is 18 AND
the customer buys paper AND
the customer buys a hole punch
THEN the customer buys a binder
The rule states that 18-year-old customers who purchase paper and a hole punch will often buy a binder at the same time. This rule would have been generated directly from a data set. Using this information the retailer may decide, for example, to create a package of products for college students.
Associative rules have a number of advantages:
There are three primary limitations to this method: