The K-L Expansion as an Effective Feature Ordering Technique for Limited Training Sample Size

An effective feature ordering technique is experimentally studied in cases where the number of training samples is limited in classifying multivariate two-class normal distributions. Several experimental results on the Hughes phenomenon using this ordering technique are presented, particularly in si...

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Bibliographic Details
Published in:IEEE transactions on geoscience and remote sensing 1983-10, Vol.GE-21 (4), p.438-441
Main Authors: Muasher, Marwan Jamil, Landgrebe, David A.
Format: Article
Language:English
Subjects:
Accuracy
Aircraft
Gaussian distribution
Infrared spectra
Laboratories
Minerals
Petroleum
Remote sensing
Statistics
Tellurium
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Summary:An effective feature ordering technique is experimentally studied in cases where the number of training samples is limited in classifying multivariate two-class normal distributions. Several experimental results on the Hughes phenomenon using this ordering technique are presented, particularly in situations where the number of training samples is only slightly higher than the number of dimensions.
ISSN:0196-2892
1558-0644
DOI:10.1109/TGRS.1983.350505