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Feature Extraction pp 119–136Cite as

Search Strategies

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Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 207))

Abstract

In order to make a search for good variable subsets, one has to know which subsets are good and which are not. In other words, an evaluation mechanism for an individual variable subset needs to be defined first.

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Author information

Authors and Affiliations

  1. ABB, Web Imaging Systems, P.O. Box 94, 00381, Helsinki, Finland

    Juha Reunanen

Authors
  1. Juha Reunanen
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Editor information

Editors and Affiliations

  1. Clopinet, 955 Creston Road, 94708, Berkeley, USA

    Isabelle Guyon

  2. Department of Electrical Engineering & Computer Science — EECS, University of California, 94720, Berkeley, USA

    Masoud Nikravesh

  3. School of Electronics and Computer Sciences, University of Southampton, SO17 1BJ, Southampton Highfield, UK

    Steve Gunn

  4. Division of Computer Science Lab. Electronics Research, University of California, Soda Hall 387, 94720-1776, Berkeley, CA, USA

    Lotfi A. Zadeh

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© 2006 Springer-Verlag Berlin Heidelberg

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Reunanen, J. (2006). Search Strategies. In: Guyon, I., Nikravesh, M., Gunn, S., Zadeh, L.A. (eds) Feature Extraction. Studies in Fuzziness and Soft Computing, vol 207. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-35488-8_5

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  • DOI: https://doi.org/10.1007/978-3-540-35488-8_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-35487-1

  • Online ISBN: 978-3-540-35488-8

  • eBook Packages: EngineeringEngineering (R0)

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