On Extensions to Fisher's Linear Discriminant Function
This correspondence describes extensions to Fisher's linear discriminant function which allow both differences in class means and covariances to be systematically included in a process for feature reduction. It is shown how the Fukunaga-Koontz transform can be combined with Fisher's method...
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 9(1987), 2 vom: 01. Feb., Seite 321-5 |
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| 1. Verfasser: | |
| Format: | Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
1987
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence |
| Schlagworte: | Journal Article |
| Zusammenfassung: | This correspondence describes extensions to Fisher's linear discriminant function which allow both differences in class means and covariances to be systematically included in a process for feature reduction. It is shown how the Fukunaga-Koontz transform can be combined with Fisher's method to allow a reduction of feature space from many dimensions to two. Performance is seen to be superior in general to the Foley-Sammon method. The technique is developed to show how a new radius vector (or pair of radius vectors) can be combined with Fisher's vector to produce a classifier with even more power of discrimination. Illustrations of the technique show that good discrimination can be obtained even if there is considerable overlap of classes in any one projection |
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| Beschreibung: | Date Completed 02.10.2012 Date Revised 12.11.2019 published: Print Citation Status PubMed-not-MEDLINE |
| ISSN: | 1939-3539 |