Projection Pursuit for Exploratory Supervised Classification
- 1 December 2005
- journal article
- Published by Informa UK Limited in Journal of Computational and Graphical Statistics
- Vol. 14 (4), 831-846
- https://doi.org/10.1198/106186005x77702
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. This article introduces new indices derived from linear discriminant analysis that can be used for exploratory supervised classification.Keywords
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