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International Conference on Artificial Intelligence and Soft Computing

ICAISC 2019: Artificial Intelligence and Soft Computing pp 319–326Cite as

Experimental Study of Totally Optimal Decision Rules

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11509))

Abstract

In this paper, we experimentally study the existence of totally optimal decision rules which are optimal relative to the length and coverage simultaneously for nine decision tables from the UCI Machine Learning Repository. Totally optimal rules can be useful when we consider decision rules as a way for knowledge representation. We study not only exact but also approximate decision rules based on the three uncertainty measures: entropy, Gini index, and misclassification error. To investigate the existence of totally optimal rules, we use an extension of dynamic programming that allows us to make multi-stage optimization of decision rules relative to the length and coverage. Experimental results show that totally optimal decision rules exist in many cases. However, the behavior of graphs describing how the number of rows of decision tables with totally optimal decision rules depends on the accuracy of rules is irregular.

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Acknowledgments

Research reported in this publication was supported by King Abdullah University of Science and Technology (KAUST).

The authors are greatly indebted to the anonymous reviewer for useful comments.

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Authors and Affiliations

  1. Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia

    Mohammad Azad & Mikhail Moshkov

Authors
  1. Mohammad Azad
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  2. Mikhail Moshkov
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Corresponding author

Correspondence to Mikhail Moshkov .

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  3. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  4. University of Alberta, Edmonton, AB, Canada

    Witold Pedrycz

  5. AGH University of Science and Technology, Kraków, Poland

    Ryszard Tadeusiewicz

  6. University of Louisville, Louisville, KY, USA

    Jacek M. Zurada

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Azad, M., Moshkov, M. (2019). Experimental Study of Totally Optimal Decision Rules. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2019. Lecture Notes in Computer Science(), vol 11509. Springer, Cham. https://doi.org/10.1007/978-3-030-20915-5_29

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  • DOI: https://doi.org/10.1007/978-3-030-20915-5_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-20914-8

  • Online ISBN: 978-3-030-20915-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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