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On the Median and Its Extensions

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Computational Intelligence for Knowledge-Based Systems Design (IPMU 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6178))

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Abstract

We review various representations of the median and related aggregation functions. An advantage of the median is that it discards extreme values of the inputs, and hence exhibits a better central tendency than the arithmetic mean. However the value of the median depends on only one or two central inputs. Our aim is to design median-like aggregation functions whose value depends on several central inputs. Such functions will preserve the stability of the median against extreme values, but will take more inputs into account. A method based on graduation curves is presented.

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Author information

Authors and Affiliations

  1. School of Information Technology, Deakin University, Australia

    Gleb Beliakov

  2. Departamento de Automática y Computación, Universidad Pública de Navarra, Pamplona, Spain

    Humberto Bustince & Javier Fernandez

Authors
  1. Gleb Beliakov
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  2. Humberto Bustince
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  3. Javier Fernandez
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Editor information

Editors and Affiliations

  1. Fachbereich Mathematik und Informatik, Philipps-Universität Marburg, Hans-Meerwein-Str., 35032, Marburg, Germany

    Eyke Hüllermeier

  2. Fakultät Informatik, Otto-von-Guericke-Universität Magdeburg, Universitätsplatz 2, 39106, Magdeburg, Germany

    Rudolf Kruse

  3. Fakultät für Elektrotechnik und Informationstechnik, Technische Universität Dortmund, Otto-Hahn-Str. 4, 44227, Dortmund, Germany

    Frank Hoffmann

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© 2010 Springer-Verlag Berlin Heidelberg

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Beliakov, G., Bustince, H., Fernandez, J. (2010). On the Median and Its Extensions. In: Hüllermeier, E., Kruse, R., Hoffmann, F. (eds) Computational Intelligence for Knowledge-Based Systems Design. IPMU 2010. Lecture Notes in Computer Science(), vol 6178. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14049-5_45

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  • DOI: https://doi.org/10.1007/978-3-642-14049-5_45

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14048-8

  • Online ISBN: 978-3-642-14049-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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