Covariance matrix estimation and classification with limitedtraining data
Hoffbeck, J.P.
Landgrebe, D.A.
AT&T Bell Labs., Whippany, NJ;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: Jul 1996
Volume: 18,
Issue: 7
On page(s): 763-767
ISSN: 0162-8828
References Cited: 6
CODEN: ITPIDJ
INSPEC Accession Number: 5349789
Digital Object Identifier: 10.1109/34.506799
Current Version Published: 2002-08-06
Abstract
A new covariance matrix estimator useful for designing classifiers
with limited training data is developed. In experiments, this estimator
achieved higher classification accuracy than the sample covariance
matrix and common covariance matrix estimates. In about half of the
experiments, it achieved higher accuracy than regularized discriminant
analysis, but required much less computation
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