Apriori Algorithm

The Apriori algorithm is used to build association models. Associations are calculated in two steps:

  1. Find all combinations of items, called frequent itemsets, whose support is greater than minimum support.
  2. Use the frequent itemsets to generate the desired rules.

ODM Association supports single-consequent rules only (for example, "ABC implies D").

The number of frequent itemsets is controlled by the minimum support parameters. The number of rules generated is controlled by the number of frequent itemsets and the confidence parameter. If the confidence parameter is set too high, there may be frequent itemsets in the association model but no rules.

Difficult Cases for Associations

The Apriori algorithm works by iteratively enumerating frequent itemsets of increasing lengths subject to the minimum support threshold. Since state-of-the-art algorithms for associations work by iterative enumeration, association rules algorithms do not handle the following cases efficiently:

For more information, see ODM Concepts in Where to Find More Information.