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Ist ein fairer Vergleich von Data Mining Algorithmen möglich?

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Data Mining

Part of the book series: Beiträge zur Wirtschaftsinformatik ((WIRTSCH.INFORM.,volume 27))

Zusammenfassung

Das Ziel dieser Arbeit ist es, DEA (Data Envelopment Analysis) zum Vergleich von Data-Mining-Algorithmen (DM-Algorithmen) einzusetzen. Die theoretischen Grundlagen werden zuerst dargestellt und es wird gezeigt, wie das DEA-Konzept, als eine Multi-Kriteria-Metrik, zum Vergleich von DM-Algorithmen verwendet werden kann. Anhand eines Beispiels aus der Literatur werden die Anwendungsmöglichkeiten der DEA dargestellt und analysiert.

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Author information

Authors and Affiliations

  1. Abteilung für Industrielle Informationsverarbeitung, Wirtschaftsuniversität Wien, Pappenheimg. 35/3, A-1200, Wien, Österreich

    W. Jammernegg

  2. Institut für Ökonometrie, Operations Research und Systemtheorie, Technische Universität Wien, Argentinierstr. 8/119, A-1040, Wien, Österreich

    M. Luptáčik & A. Schnabl

  3. Forschung und Entwicklung, Daimler-Benz AG, Postfach 2360, D-89013, Ulm, Deutschland

    G. Nakhaeizadeh

Authors
  1. W. Jammernegg
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  2. M. Luptáčik
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  3. G. Nakhaeizadeh
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  4. A. Schnabl
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Editor information

Editors and Affiliations

  1. Forschung und Technik, Daimler-Benz AG, Postfach 2360, D-89013, Ulm, Deutschland

    Gholamreza Nakhaeizadeh

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© 1998 Physica-Verlag Heidelberg

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Jammernegg, W., Luptáčik, M., Nakhaeizadeh, G., Schnabl, A. (1998). Ist ein fairer Vergleich von Data Mining Algorithmen möglich?. In: Nakhaeizadeh, G. (eds) Data Mining. Beiträge zur Wirtschaftsinformatik, vol 27. Physica-Verlag HD. https://doi.org/10.1007/978-3-642-86094-2_13

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  • DOI: https://doi.org/10.1007/978-3-642-86094-2_13

  • Publisher Name: Physica-Verlag HD

  • Print ISBN: 978-3-7908-1053-0

  • Online ISBN: 978-3-642-86094-2

  • eBook Packages: Springer Book Archive

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