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On the computation of the Kullback-Leibler measure for spectral distances

โœ Scribed by Veldhuis, R.; Klabbers, E.


Book ID
117935763
Publisher
IEEE
Year
2003
Tongue
English
Weight
292 KB
Volume
11
Category
Article
ISSN
1063-6676

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A frequent practice in feature selection is to maximize the Kullback-Leibler (K-L) distance between target classes. In this note we show that this common custom is frequently suboptimal, since it fails to take into account the fact that classification occurs using a finite number of samples. In clas