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Harnessing Classifier Networks – Towards Hierarchical Concept Construction

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Rough Sets and Current Trends in Computing (RSCTC 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3066))

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Abstract

The process of construction and tuning of classifier networks is discussed. The idea of relating the basic inputs with the target classification concepts via the internal layers of intermediate concepts is explored. Intuitions and relationships to other approaches, as well as the illustrative examples are provided.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Regina, Regina, SK, S4S 0A2, Canada

    Dominik Ślezak

  2. Polish-Japanese Institute of Information Technology, Koszykowa 86, 02-008, Warsaw, Poland

    Dominik Ślezak & Jakub Wróblewski

  3. Institute of Mathematics, Warsaw University, Banacha 2, 02-097, Warsaw, Poland

    Marcin S. Szczuka

Authors
  1. Dominik Ślezak
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  2. Marcin S. Szczuka
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  3. Jakub Wróblewski
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Editor information

Editors and Affiliations

  1. Shimane University, 89-1 Enya-cho Izumo, 6938501, Shimane, Japan

    Shusaku Tsumoto

  2. Systems Research Institute, Polish Academy of Sciences, 01-447, Warsaw, Poland

    Roman Słowiński

  3. The Linnaeus Centre for Bioinformatics, Uppsala University, Uppsala, Sweden

    Jan Komorowski

  4. Institute of Computer Science, Polish Academy of Sciences, 01–237, Warsaw, Poland

    Jerzy W. Grzymała-Busse

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© 2004 Springer-Verlag Berlin Heidelberg

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Ślezak, D., Szczuka, M.S., Wróblewski, J. (2004). Harnessing Classifier Networks – Towards Hierarchical Concept Construction. In: Tsumoto, S., Słowiński, R., Komorowski, J., Grzymała-Busse, J.W. (eds) Rough Sets and Current Trends in Computing. RSCTC 2004. Lecture Notes in Computer Science(), vol 3066. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25929-9_67

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  • DOI: https://doi.org/10.1007/978-3-540-25929-9_67

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22117-3

  • Online ISBN: 978-3-540-25929-9

  • eBook Packages: Springer Book Archive

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