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Comparing Partitions by Means of Fuzzy Data Mining Tools

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Scalable Uncertainty Management (SUM 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7520))

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Abstract

Rand index is one of the most popular measures for comparing two partitions over a set of objects. Several approaches have extended this measure for those cases involving fuzzy partitions. In previous works, we developed a methodology for correspondence analysis between partitions in terms of data mining tools. In this paper we discuss how, without any additional cost, it can be applied as an alternate computation of Rand index, allowing us not only to compare both crisp and fuzzy partitions, but also classes inside these partitions.

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Author information

Authors and Affiliations

  1. Dept of Computer Science, University of Jaén, Spain

    Carlos Molina & José-María Serrano

  2. Dept. Software Engineering, University of Granada, Spain

    Belén Prados

  3. Dept. Computer Science and A.I., University of Granada, Spain

    María-Dolores Ruiz

  4. European Centre for Soft Computing, Mieres, Spain

    Daniel Sánchez

Authors
  1. Carlos Molina
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  2. Belén Prados
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  3. María-Dolores Ruiz
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  4. Daniel Sánchez
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  5. José-María Serrano
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Editor information

Editors and Affiliations

  1. Department of Mathematics and Computer Science, Marburg University, Hans-Meerwein-Strasse 6, 35032, Marburg, Germany

    Eyke Hüllermeier , Thomas Fober  & Bernhard Seeger ,  & 

  2. Department of Computer Science, Auckland University, 38 Princes St., 1010, Auckland, New Zealand

    Sebastian Link

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© 2012 Springer-Verlag Berlin Heidelberg

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Molina, C., Prados, B., Ruiz, MD., Sánchez, D., Serrano, JM. (2012). Comparing Partitions by Means of Fuzzy Data Mining Tools. In: Hüllermeier, E., Link, S., Fober, T., Seeger, B. (eds) Scalable Uncertainty Management. SUM 2012. Lecture Notes in Computer Science(), vol 7520. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33362-0_26

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  • DOI: https://doi.org/10.1007/978-3-642-33362-0_26

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33361-3

  • Online ISBN: 978-3-642-33362-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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