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Knowledge Extraction Through Learning from Examples

  • Igor Mozetic
Part of the The Kluwer International Series in Engineering and Computer Science book series (SECS, volume 12)

Abstract

We present a method for a knowledge-base compression, restricted to rules of specific form, which uses a learning from examples facility. A large medical knowledge-base, which was a source of more than 5000 training examples, was compressed to 3% of its original size. Most of the extracted rules turned out to be quite meaningful from the medical point of view.

Keywords

Decision Variable Disjunctive Normal Form Decision Class Inductive Learning Heart Disorder 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Kluwer Academic Publishers 1986

Authors and Affiliations

  • Igor Mozetic
    • 1
  1. 1.Department of Computer ScienceUniversity of Illinois at Urbana-ChampaignUrbanaUSA

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