Small sample size effects in statistical pattern recognition:recommendations for practitioners
Raudys, S.J.
Jain, A.K.
Inst. of Math. & Cybern., Acad. of Sci., Vilnius, Lithuanian SSR;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: Mar 1991
Volume: 13,
Issue: 3
On page(s): 252-264
ISSN: 0162-8828
References Cited: 58
CODEN: ITPIDJ
INSPEC Accession Number: 3920500
Digital Object Identifier: 10.1109/34.75512
Current Version Published: 2002-08-06
Abstract
The effects of sample size on feature selection and error
estimation for several types of classifiers are discussed. The focus is
on the two-class problem. Classifier design in the context of small
design sample size is explored. The estimation of error rates under
small test sample size is given. Sample size effects in feature
selection are discussed. Recommendations for the choice of learning and
test sample sizes are given. In addition to surveying prior work in this
area, an emphasis is placed on giving practical advice to designers and
users of statistical pattern recognition systems
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