While boosting seems to provide larger gains in accuracy, the price to pay is that the learned ensemble of classifiers is no longer easy to comprehend. While round robin rule learning also learns an ensemble of classifiers, we think that it has the advantage that each element of the ensemble has a well-defined semantics (separating two classes from each other). In fact, Pyle (1999, p.16) proposes a very similar technique called pairwise ranking in order to facilitate human decision-making in ranking problems. He claims that it is easier for a human to determine an order between n items if one makes pairwise comparisons between the individual items and then adds up the wins for each item, instead of trying to order the items right away.15