The association rule learner* searches for frequent itemsets meeting the user-defined minimum
support criterion and, optionally, creates association rules from
them. The column containing the transactions (BitVectors or
Collections) has to be selected. The minimum
support as an absolute number must be provided (therefore check the number
of transactions to obtain a sensible criterion). If the frequent itemsets
should be free (unconstrained) or closed or maximal has also be defined.
Closed itemsets are frequent itemsets, which have no superset with the
same support, thus providing all the information from free itemsets
in a compressed form. Maximal itemsets are sets which have no
frequent superset at all. The maximal itemset length must also be
defined. If association rules are generated, a confidence value has to be
provided. The confidence is a value to define how often the rule is
right. Association rules generated here are in the form to have only one
item in the consequence.
The underlying data structure used by the algorithm can be either an
ARRAY or a TIDList. Choose the former when there are many
transactions an less items, and the latter if the structure of the
input data is vice versa.
(*) RULE LEARNER is a registered trademark of Minitab, LLC and is used with Minitab’s permission.
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