Machine Learning

, Volume 3, Issue 4, pp 261–283 | Cite as

The CN2 Induction Algorithm

  • Peter Clark
  • Tim Niblett

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.

Concept learning rule induction noise comprehensibility 

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Copyright information

© Kluwer Academic Publishers 1989

Authors and Affiliations

  • Peter Clark
  • Tim Niblett

There are no affiliations available

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