In association rule mining, the process of extracting relations from a dataset often requires
the application of more than one quality measure and, in many cases, such measures
involve conflicting objectives. In such a situation, it is more appropriate to attain the optimal
trade-off between measures. This paper deals with the association rule mining problem
under a multi-objective perspective by proposing grammar guided genetic programming
(G3P) models, that enable the extraction of both numerical and nominal association rules in …