Journal of Machine Learning Research vol:4 issue:Aug pages:465-491
Relatively simple transformations can speed up the execution of queries for data mining considerably. While some ILP systems use such transformations, little is known about them or how they relate to each other. The paper describes a number of such transformations. Not all of them are novel, but there have been no studies comparing their efficacy. The main contributions of the paper are: (a) it clarifies the relationship between the transformations; (b) it contains an empirical study of what can be gained by applying the transformations; (c) it provides some guidance on the kinds of problems that are likely to benefit from the transformations.