Feature Extraction for Nonparametric Discriminant Analysis
In high-dimensional classification problems, one is often interested in finding a few important discriminant directions in order to reduce the dimensionality. Fisher's linear discriminant analysis (LDA) is a commonly used method. Although LDA is guaranteed to find the best directions when each...
| Veröffentlicht in: | Journal of Computational and Graphical Statistics. - American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America, 1992. - 12(2003), 1, Seite 101-120 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
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2003
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| Zugriff auf das übergeordnete Werk: | Journal of Computational and Graphical Statistics |
| Schlagworte: | Classification Density estimation Dimension reduction LDA Projection pursuit Reduced-rank model SAVE Mathematics Physical sciences Political science mehr... |
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