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Man–Machine Interactions 4 pp 639–650Cite as

Optimization of Decision Rules Relative to Coverage—Comparison of Greedy and Modified Dynamic Programming Approaches

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 391))

Abstract

In the paper, a modification of a dynamic programming algorithm for optimization of decision rules relative to coverage is proposed. Experimental results with decision tables from UCI Machine Learning Repository are presented.

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References

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Author information

Authors and Affiliations

  1. Institute of Computer Science, University of Silesia, Sosnowiec, Poland

    Beata Zielosko

Authors
  1. Beata Zielosko
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Correspondence to Beata Zielosko .

Editor information

Editors and Affiliations

  1. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Aleksandra Gruca

  2. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Agnieszka Brachman

  3. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Stanisław Kozielski

  4. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Tadeusz Czachórski

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Zielosko, B. (2016). Optimization of Decision Rules Relative to Coverage—Comparison of Greedy and Modified Dynamic Programming Approaches. In: Gruca, A., Brachman, A., Kozielski, S., Czachórski, T. (eds) Man–Machine Interactions 4. Advances in Intelligent Systems and Computing, vol 391. Springer, Cham. https://doi.org/10.1007/978-3-319-23437-3_55

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  • DOI: https://doi.org/10.1007/978-3-319-23437-3_55

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23436-6

  • Online ISBN: 978-3-319-23437-3

  • eBook Packages: EngineeringEngineering (R0)

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