Functional Dependencies with Predicates: What Makes the g3-error Easy to Compute?

The notion of functional dependencies (FDs) can be used by data scientists and domain experts to confront background knowledge against data. To overcome the classical, too restrictive, satisfaction FDs, it is possible replace equality with more meaningful binary predicates, use a coverage measure such as $$g_3$$ -error estimate degree which FD matches It known that computed in polynomial time if used, but unfortunately, problem becomes NP-complete when relying on general predicates instead. However, there has been no analysis class or properties alter complexity problem, especially going from predicates. In this work, we provide an analysis. We focus commonly equality, similarity relations, partial orders. These are: reflexivity, transitivity, symmetry, antisymmetry. show symmetry transitivity together are sufficient guarantee time. dropping either them makes NP-complete.