The RISE System: Conquering without Separating

Current rule induction systems (e.g. CN2) typically rely on a \separate and conquer" strategy, learning each rule only from still-uncovered examples. This results in a dwindling number of examples being available for learning successive rules, adversely a ecting the system's accuracy. An alternative is to learn all rules simultaneously, using the entire training set for each. This approach is implemented in the Rise 1.0 system. Empirical comparison of Rise with CN2 suggests that \conquering without separating" performs similarly to its counterpart in simple domains, but achieves increasingly substantial gains in accuracy as the domain di culty grows.