Pruning Methods for Rule Learning Algorithms

In this paper we will shortly review several pruning methods for rela-tional learning algorithms and show how they are related to each other. We then report some experiments in several natural domains and try to analyse the performance of the algorithms in these domains in terms of run-time and accuracy. While some algorithms are clearly faster than others, no safe recommendation for achieving high accuracy can be given.