Arbeitspapier

Projection pursuit for exploratory supervised classification

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In high-dimensional data, one often seeks a few interesting low-dimensional projections that reveal important features of the data. Projection pursuit is a procedure for searching high-dimensional data for interesting low-dimensional projections via the optimization of a criterion function called the projection pursuit index. Very few projection pursuit indices incorporate class or group information in the calculation. Hence, they cannot be adequately applied in supervised classification problems to provide low-dimensional projections revealing class differences in the data. We introduce new indices derived from linear discriminant analysis that can be used for exploratory supervised classification.

Sprache
Englisch

Erschienen in
Series: SFB 649 Discussion Paper ; No. 2005,026

Klassifikation
Wirtschaft
Thema
Data mining
Exploratory multivariate data analysis
Gene expression data
Discriminant analysis

Ereignis
Geistige Schöpfung
(wer)
Lee, Eun-Kyung
Cook, Dianne
Klinke, Sigbert
Lumley, Thomas
Ereignis
Veröffentlichung
(wer)
Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk
(wo)
Berlin
(wann)
2005

Handle
Letzte Aktualisierung
10.03.2025, 11:42 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
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Objekttyp

  • Arbeitspapier

Beteiligte

  • Lee, Eun-Kyung
  • Cook, Dianne
  • Klinke, Sigbert
  • Lumley, Thomas
  • Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk

Entstanden

  • 2005

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