This paper presents an approach to visualizing and exploring high-dimensional rules in two-dimensional views. The proposed method uses multi-dimensional scaling to place the rule centers and subsequently extends the rules' regions to depict their overlap. This results not only in a visualization of the rules' distribution but also enables the relationship to their immediate neighbors to be judged. The proposed technique is illustrated and discussed on a number of well-known benchmark data sets.