Machine Learning

, Volume 3, Issue 4, pp 261–283

The CN2 Induction Algorithm


  • Peter Clark
  • Tim Niblett

DOI: 10.1023/A:1022641700528

Cite this article as:
Clark, P. & Niblett, T. Machine Learning (1989) 3: 261. doi:10.1023/A:1022641700528


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

Copyright information

© Kluwer Academic Publishers 1989