The "exclusive or" function has a long and arduous history in the AI/machine learning communities. From my understanding of "association rule learning", xor would appear to be a problem for this type of learning. That is, suppose we have the following data:
A B C 0 0 0 0 1 1 1 0 1 1 1 0
Clearly the rule I would seek from this data is that $A\oplus B = C$. However, it is my undnerstanding that association rule learning techniques would instead discover the rules $A \Rightarrow C$ and $B \Rightarrow C$ each with 50% confidence.
Is my assessment correct that this is a known issue within association rule learning, and if so, are there standard ways of handling such issues? I can imagine some workarounds, but I'm not sure they fit within the context of association rule learning.