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Learning Rule Sets

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Book cover Foundations of Rule Learning

Part of the book series: Cognitive Technologies ((COGTECH))

Abstract

The main shortcoming of algorithms for learning a single rule is the lack of expressiveness of a single conjunctive rule. In this chapter we present approaches that construct sets of rules. These sets can be constructed by iterative usage of the algorithms for constructing single rules presented in Chap. 6.

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Notes

  1. 1.

    One may say that Precision assumes a different cost model for each point in the space, depending on the relative frequencies of the covered positive and negative examples. Such local changes of cost models are investigated in more detail by Flach (2003).

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Authors and Affiliations

  1. FB Informatik, TU Darmstadt, Darmstadt, Germany

    Johannes Fürnkranz

  2. Rudjer Bošković Institute, Zagreb, Croatia

    Dragan Gamberger

  3. Department of Knowledge Technologies, Jožef Stefan Institute, Ljubljana, Slovenia

    Nada Lavrač

Authors
  1. Johannes Fürnkranz
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  2. Dragan Gamberger
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  3. Nada Lavrač
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© 2012 Springer-Verlag Berlin Heidelberg

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Fürnkranz, J., Gamberger, D., Lavrač, N. (2012). Learning Rule Sets. In: Foundations of Rule Learning. Cognitive Technologies. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75197-7_8

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  • DOI: https://doi.org/10.1007/978-3-540-75197-7_8

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