Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/25045 
Erscheinungsjahr: 
2005
Schriftenreihe/Nr.: 
SFB 649 Discussion Paper No. 2005,026
Verlag: 
Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk, Berlin
Zusammenfassung: 
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.
Schlagwörter: 
Data mining
Exploratory multivariate data analysis
Gene expression data
Discriminant analysis
Dokumentart: 
Working Paper

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