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DNA Rough-Set Computing in the Development of Decision Rule Reducts

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Rough Sets and Intelligent Systems - Professor Zdzisław Pawlak in Memoriam

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 42))

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Abstract

Rough set methods are often employed for reducting decision rules. The specific techniques involving rough sets can be carried out in a computational manner. However, they are quite demanding when it comes computing overhead. In particular, it becomes problematic to compute all minimal length decision rules while dealing with a large number of decision rules. This results in an NP-hard problem. To address this computational challenge, in this study, we propose a method of DNA rough-set computing composed of computational DNA molecular techniques used for decision rule reducts. This method can be effectively employed to alleviate the computational complexity of the problem.

This book chapter has been prepared on a basis of the results of the paper, entitled “A DNA-based algorithm for minimizing decision rules: a rough sets approach” to be published in IEEE Transactions on NanoBioscience at the end of 2011.

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Author information

Authors and Affiliations

  1. Graduate School of Information, Production and Systems, Waseda University, Kitakyushu, 808-0135, Japan

    Ikno Kim & Junzo Watada

  2. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, T6R 2G7, Canada

    Witold Pedrycz

Authors
  1. Ikno Kim
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  2. Junzo Watada
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  3. Witold Pedrycz
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Correspondence to Ikno Kim .

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Editors and Affiliations

  1. Institute of Mathematics, Warsaw University, Banacha 2, Warsaw, 02097, Poland

    Andrzej Skowron

  2. Institute of Computer Science, University of Rzeszów, ul. Dekerta 2, Rzeszów, 35-030, Poland

    Zbigniew Suraj

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Kim, I., Watada, J., Pedrycz, W. (2013). DNA Rough-Set Computing in the Development of Decision Rule Reducts. In: Skowron, A., Suraj, Z. (eds) Rough Sets and Intelligent Systems - Professor Zdzisław Pawlak in Memoriam. Intelligent Systems Reference Library, vol 42. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30344-9_15

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  • DOI: https://doi.org/10.1007/978-3-642-30344-9_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-30343-2

  • Online ISBN: 978-3-642-30344-9

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