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International Conference on Intelligent Data Engineering and Automated Learning

IDEAL 2002: Intelligent Data Engineering and Automated Learning — IDEAL 2002 pp 493–499Cite as

Usage of New Information Estimations for Induction of Fuzzy Decision Trees

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2412))

Abstract

We introduce a technique to compute new summary information estimations (information and entropy) for fuzzy sets. Special features for these estimations are investigated. We give an algorithm for determine various information measures for fuzzy sets and fuzzy decision trees. Finally, we are using our estimations for induction of fuzzy decision trees from a group of training examples.

This investigation has been supported by the grant 01M-122 of Fund of Fundamental Researches and grant of Ministry of Education (Republic of Belarus).

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Author information

Authors and Affiliations

  1. Dept. of Information Technologies, Belarussian State Economic University, Partizan ave 26, 220672, Minsk, Belarus

    Vitaly G. Levashenko & Elena N. Zaitseva

  2. Dept. of Informatics, Faculty of Management Science and Informatics, University of ilina, Moyzesova 20, 01026, ilina, Slovakia

    Vitaly G. Levashenko

Authors
  1. Vitaly G. Levashenko
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  2. Elena N. Zaitseva
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Editor information

Editors and Affiliations

  1. Department of Electrical Engineering and Electronics, UMIST, Manchester, M60 1QD, UK

    Hujun Yin , Nigel Allinson  & Richard Freeman ,  & 

  2. Department of Computation, UMIST, Manchester, M60 1QD, UK

    John Keane

  3. Department of Biomolecular Science, UMIST, Manchester, M60 1QD, UK

    Simon Hubbard

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© 2002 Springer-Verlag Berlin Heidelberg

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Levashenko, V.G., Zaitseva, E.N. (2002). Usage of New Information Estimations for Induction of Fuzzy Decision Trees. In: Yin, H., Allinson, N., Freeman, R., Keane, J., Hubbard, S. (eds) Intelligent Data Engineering and Automated Learning — IDEAL 2002. IDEAL 2002. Lecture Notes in Computer Science, vol 2412. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45675-9_74

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  • DOI: https://doi.org/10.1007/3-540-45675-9_74

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44025-3

  • Online ISBN: 978-3-540-45675-9

  • eBook Packages: Springer Book Archive

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