As such, they can also be seen as a list of "if-then" clauses: if the record matches some criteria (expressed in the left side of the rule, also called antecedent), it is then labeled accordingly to the class on the right side of the rule (or consequent).
[3] Metrics can be used to order or filter the rules in the model[4] and to evaluate their quality.
The first proposal of a classification model made of association rules was FBM.
The approach was popularized by CBA,[1] although other authors had also previously proposed the mining of association rules for classification.
[5] Other authors have since then proposed multiple changes to the initial model, like the addition of a redundant rule pruning phase[6] or the exploitation of Emerging Patterns.