Learning Logical Definitions from Relations |
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| Authors: | JR Quinlan |
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| Affiliation: | (1) Basser Department of Computer Science, University of Sydney, Sydney, NSW, Australia 2006 |
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| Abstract: | This paper describes FOIL, a system that learns Horn clauses from data expressed as relations. FOIL is based on ideas that have proved effective in attribute-value learning systems, but extends them to a first-order formalism. This new system has been applied successfully to several tasks taken from the machine learning literature. |
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| Keywords: | Induction first-order rules relational data empirical learning |
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