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OFAI-TR-93-28 ( 88kB g-zipped PostScript file)

FOSSIL: A robust relational learner

Johannes Fürnkranz

The research reported in this paper describes FOSSIL, an ILP system that uses a search heuristic based on statistical correlation. Several interesting properties of this heuristic are discussed, and a it is shown how it naturally can be extended with a simple, but powerful stopping criterion that is independent of the number of training examples. Instead, FOSSIL's stopping criterion depends on a search heuristic that estimates the utility of literals on a uniform scale. After a comparison with FOIL and mFOIL in the KRK domain and on the mesh data, we outline some ideas how FOSSIL can be adopted for top-down pruning and present some preliminary results.

Citation: Fürnkranz J.: FOSSIL: A robust relational learner, An extended version of the paper in Proc. European Conf. on Machine Learning, ECML-94, pp. 122-137, Catania, Italy, Springer-Verlag, 1994.