Learning Logical Definitions from Relations

  • Authors:
  • J. R. Quinlan

  • Affiliations:
  • Basser Department of Computer Science, University of Sydney, Sydney NSW Australia 2006

  • Venue:
  • Machine Learning
  • Year:
  • 1990

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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.