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Classification Based on the Support Vector Machine and on Regression Depth

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Part of the Statistics for Industry and Technology book series (SIT)

Abstract

This paper compares modern classification methods based on the support vector machine (SVM) and on the regression depth method (RDM) with classical linear and quadratic discriminant analysis.

Keywords

  • Support Vector Machine
  • Test Error
  • Response Group
  • Full Column Rank
  • Quadratic Discriminant Analysis

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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  • DOI: 10.1007/978-3-0348-8201-9_28
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© 2002 Springer Basel AG

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Christmann, A. (2002). Classification Based on the Support Vector Machine and on Regression Depth. In: Dodge, Y. (eds) Statistical Data Analysis Based on the L1-Norm and Related Methods. Statistics for Industry and Technology. Birkhäuser, Basel. https://doi.org/10.1007/978-3-0348-8201-9_28

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  • DOI: https://doi.org/10.1007/978-3-0348-8201-9_28

  • Publisher Name: Birkhäuser, Basel

  • Print ISBN: 978-3-0348-9472-2

  • Online ISBN: 978-3-0348-8201-9

  • eBook Packages: Springer Book Archive