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Rank Correlation Coefficient Correction by Removing Worst Cases

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Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Methods (IPMU 2010)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 80))

Abstract

Rank correlation can be used to compare two linearly ordered rankings. If the rankings include noise values, the rank correlation coefficient will yield lower values than it actually should. In this paper, we propose an algorithm to remove pairs of values from rankings in order to increase Kendall’s tau rank correlation coefficient. The problem itself is motivated from real data in bioinformatics context.

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References

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Author information

Authors and Affiliations

  1. Department of Computer Science, Ostfalia University of Applied Sciences, Salzdahlumer Str. 46/48, D-38302, Wolfenbuettel, Germany

    Martin Krone & Frank Klawonn

  2. Bioinformatics and Statistics, Helmholtz Centre for Infection Research, Inhoffenstr. 7, D-38124, Braunschweig, Germany

    Frank Klawonn

Authors
  1. Martin Krone
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  2. Frank Klawonn
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Editor information

Editors and Affiliations

  1. Fachbereich Mathematik und Informatik, Philipps-Universität Marburg, Marburg, Germany

    Eyke Hüllermeier

  2. Department of Knowledge Processing and Language Engineering, Otto-von-Guericke University of Magdeburg, Universitätsplatz 2, 39106, Magdeburg, Germany

    Rudolf Kruse

  3. Fakultät für Elektrotechnik und Informationstechnik, Technische Universität Dortmund, 44221, Dortmund, Germany

    Frank Hoffmann

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© 2010 Springer-Verlag Berlin Heidelberg

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Krone, M., Klawonn, F. (2010). Rank Correlation Coefficient Correction by Removing Worst Cases. In: Hüllermeier, E., Kruse, R., Hoffmann, F. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Methods. IPMU 2010. Communications in Computer and Information Science, vol 80. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14055-6_37

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  • DOI: https://doi.org/10.1007/978-3-642-14055-6_37

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14054-9

  • Online ISBN: 978-3-642-14055-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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