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Choosing the Right Lens: Finding What is Interesting in Data Mining

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Quality Measures in Data Mining

Part of the book series: Studies in Computational Intelligence ((SCI,volume 43))

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Regina, Canada

    Liqiang Geng

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

    Howard J. Hamilton

Authors
  1. Liqiang Geng
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  2. Howard J. Hamilton
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Editor information

Editors and Affiliations

  1. LINA-CNRS FRE 2729, Ecole polytechnique de l'université de Nantes, Rue Christian-Pauc-La Chantrerie, 60601, 44306, NANTES Cedex 3, France

    Fabrice J. Guillet

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

    Howard J. Hamilton

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Geng, L., Hamilton, H.J. (2007). Choosing the Right Lens: Finding What is Interesting in Data Mining. In: Guillet, F.J., Hamilton, H.J. (eds) Quality Measures in Data Mining. Studies in Computational Intelligence, vol 43. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-44918-8_1

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  • DOI: https://doi.org/10.1007/978-3-540-44918-8_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44911-9

  • Online ISBN: 978-3-540-44918-8

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