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Filtering Decision Rules with Continuous Attributes Governed by Discretisation

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Foundations of Intelligent Systems (ISMIS 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10352))

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Abstract

The paper presents research on selection of decision rules with continuous condition attributes while exploiting characteristics of these attributes obtained by supervised discretisation. The considered features were split into categories corresponding to numbers of intervals required for partitioning of their values, and this information was next used to divide the sets of rules by their conditions falling into specific categories. Also to each group of variables there was assigned some weight, basing on which several rule quality measures were calculated. They enabled filtering rules meeting requirements with respect to performance.

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Acknowledgments

The research presented in the paper was performed at the Silesian University of Technology, Gliwice, within the project BK/RAu2/2017. In the research there was used 4eMka Software [5, 9] and WEKA [14].

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Authors and Affiliations

  1. Institute of Informatics, Silesian University of Technology, Akademicka 16, 44-100, Gliwice, Poland

    Urszula Stańczyk

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  1. Urszula Stańczyk
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Correspondence to Urszula Stańczyk .

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Editors and Affiliations

  1. Warsaw University of Technology, Warsaw, Poland

    Marzena Kryszkiewicz

  2. University of Bari Aldo Moro, Bari, Italy

    Annalisa Appice

  3. Institute of Informatics, University of Warsaw, Warsaw, Poland

    Dominik Ślęzak

  4. Faculty of Electronics & Information, Warsaw University of Technology, Warsaw, Poland

    Henryk Rybinski

  5. Institute of Mathematics, Warsaw University, Warsaw, Poland

    Andrzej Skowron

  6. Department of Computer Science, University of North Carolina at Charlotte, North Carolina, USA

    Zbigniew W. Raś

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Stańczyk, U. (2017). Filtering Decision Rules with Continuous Attributes Governed by Discretisation. In: Kryszkiewicz, M., Appice, A., Ślęzak, D., Rybinski, H., Skowron, A., Raś, Z. (eds) Foundations of Intelligent Systems. ISMIS 2017. Lecture Notes in Computer Science(), vol 10352. Springer, Cham. https://doi.org/10.1007/978-3-319-60438-1_33

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  • DOI: https://doi.org/10.1007/978-3-319-60438-1_33

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60437-4

  • Online ISBN: 978-3-319-60438-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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