Machine Learning

, Volume 9, Issue 1, pp 57–94

The Utility of Knowledge in Inductive Learning

  • Michael Pazzani
  • Dennis Kibler

DOI: 10.1023/A:1022628829777

Cite this article as:
Pazzani, M. & Kibler, D. Machine Learning (1992) 9: 57. doi:10.1023/A:1022628829777


In this paper, we demonstrate how different forms of background knowledge can be integrated with an inductive method for generating function-free Horn clause rules. Furthermore, we evaluate, both theoretically and empirically, the effect that these forms of knowledge have on the cost and accuracy of learning. Lastly, we demonstrate that a hybrid explanation-based and inductive learning method can advantageously use an approximate domain theory, even when this theory is incorrect and incomplete.

Learning relationscombining inductive and explanation-based learning
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Copyright information

© Kluwer Academic Publishers 1992

Authors and Affiliations

  • Michael Pazzani
    • 1
  • Dennis Kibler
    • 1
  1. 1.Department of Information & Computer ScienceUniversity of California, IrvineIrvine