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Improving Feature Extraction by Replacing the Fisher Criterion by an Upper Error Bound

Author

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  • Weihs, Claus
  • Luebke, Karsten

Abstract

A lot of alternatives and constraints have been proposed in order to improve the Fisher criterion. But most of them are not linked to the error rate, the primary interest in many applications of classification. By introducing an upper bound for the error rate a criterion is developed which can improve the classification performance.

Suggested Citation

  • Weihs, Claus & Luebke, Karsten, 2005. "Improving Feature Extraction by Replacing the Fisher Criterion by an Upper Error Bound," Technical Reports 2005,19, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    • Handle: RePEc:zbw:sfb475:200519
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    Cited by:

    1. Karsten Luebke & Claus Weihs, 2011. "Linear dimension reduction in classification: adaptive procedure for optimum results," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 5(3), pages 201-213, October.

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