Projection pursuit for exploratory supervised classification

Eun-Kyung Lee, Dianne Cook, Sigbert Klinke and Thomas Lumley

No 2005-026, SFB 649 Discussion Papers from Humboldt University Berlin, Collaborative Research Center 649: Economic Risk

Abstract: 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.

Keywords: Data mining; Exploratory multivariate data analysis; Gene expression data; Discriminant analysis (search for similar items in EconPapers)
Date: 2005
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:sfb649:sfb649dp2005-026

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