The CN2 Induction Algorithm

  • Authors:
  • Peter Clark;Tim Niblett

  • Affiliations:
  • The Turing Institute, 36 North Hanover Street, Glasgow, G1 2AD, U.K. PETE@TURING.AC.UK;The Turing Institute, 36 North Hanover Street, Glasgow, G1 2AD, U.K. TIM@TURING.AC.UK

  • Venue:
  • Machine Learning
  • Year:
  • 1989

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Abstract

Systems for inducing concept descriptions from examples are valuable tools for assisting in the task of knowledge acquisition for expert systems. This paper presents a description and empirical evaluation of a new induction system, CN2, designed for the efficient induction of simple, comprehensible production rules in domains where problems of poor description language and/or noise may be present. Implementations of the CN2, ID3, and AQ algorithms are compared on three medical classification tasks.