Association rules

By using association rules mining, you can discover interesting and useful relations between items in a large-scale transaction table. You can identify strong rules between related items by using different measures of interestingness.

A large-scale transaction table contains transactions that consist of a set of items and a transaction identifier, for example, a market basket. Association rules are implications of the form X -> Y, where X and Y are two subsets of all available items. X is called the body or left-hand-side (LHS). Y is called the head or right-hand-side (RHS). The association rules that are discovered must satisfy user-defined constraints for measures of significance and interest.