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Construct Fuzzy Decision Trees Based on Roughness Measures

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Advances in Communication, Network, and Computing (CNC 2012)

Abstract

Data mining is a process of extracting useful patterns and regularities from large bodies of data. Decision trees (DT) is one of data mining techniques used to deal with classical data. Fuzzy Decision Trees (FDT) is generalization of crisp decision trees, which aims to combine symbolic decision trees with approximate reasoning offered by fuzzy representation. Given a fuzzy information system (FIS), fuzzy expanded attributes play a crucial role in fuzzy decision trees. In this paper the problem is slowness and complexities of the fuzzy decision trees, but its rules are more accurate. Our target is to simplify computational procedures and increase the accuracy rules or to keep the high grade of accuracy and to select an efficient criterion to select fuzzy expanded attributes based on rough set theory.

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Author information

Authors and Affiliations

  1. Computer Sciences Department, Academy of Specialized Studies, Cairo, Egypt

    Mohamed A. Elashiri

  2. Computer Sciences and Information Department, Institute of Statistics and Research, Cairo University, Egypt

    Hesham A. Hefny

  3. Computer Sciences and Systems Department, Electronics Research Institute, Cairo, Egypt

    Ashraf H. Abd Elwhab

Authors
  1. Mohamed A. Elashiri
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  2. Hesham A. Hefny
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  3. Ashraf H. Abd Elwhab
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Editor information

Editors and Affiliations

  1. Network Security Group, Institute of Doctors Engineering and Scientists (The IDES), Ouderkerk aan de Amstel, 1191 GT, Amsterdam, The Netherlands

    Vinu V. Das

  2. Ilahia College of Engineering, Kothamangalam, India

    Janahanlal Stephen

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© 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering

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Elashiri, M.A., Hefny, H.A., Abd Elwhab, A.H. (2012). Construct Fuzzy Decision Trees Based on Roughness Measures. In: Das, V.V., Stephen, J. (eds) Advances in Communication, Network, and Computing. CNC 2012. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 108. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35615-5_29

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  • DOI: https://doi.org/10.1007/978-3-642-35615-5_29

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35614-8

  • Online ISBN: 978-3-642-35615-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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