Techniques for efficient empirical induction

  • Geoffrey I. Webb
Knowledge Acquisition And Representation

DOI: 10.1007/3-540-52062-7_82

Part of the Lecture Notes in Computer Science book series (LNCS, volume 406)
Cite this paper as:
Webb G.I. (1990) Techniques for efficient empirical induction. In: Barter C.J., Brooks M.J. (eds) AI '88. AI 1988. Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence), vol 406. Springer, Berlin, Heidelberg

Abstract

This paper describes the LEI algorithm for empirical induction. The LEI algorithm provides efficient empirical induction for discrete attribute value data. It derives a classification procedure in the form of a set of predicate logic classification rules. This contrasts with the only other efficient approach to exhaustive empirical induction, the derivatives of the CLS algorithm, which present their classification procedures in the form of a decision tree. The LEI algorithm will always find the simplest non-disjunctive rule that correctly classifies all examples of a single class where such a rule exists.

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Copyright information

© Springer-Verlag 1990

Authors and Affiliations

  • Geoffrey I. Webb
    • 1
  1. 1.Division of Computing and MathematicsDeakin University

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