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Using a stopping rule to determine the size of the training sample in a classification problem

The problem of determining the size of the training sample needed to achieve sufficiently small misclassification probability is considered. The appropriate sample size is approximated using a stopping rule. The proposed procedure is asymptotically optimal.
Year of publication:
1998
Authors: Kundu, Subrata ; Martinsek, Adam T.
Published in:
Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 37.1998, 1, p. 19-27
Publisher: Elsevier
Keywords: Classification Discrimination Pattern recognition Density estimate Stopping rule
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Type of publication: Article
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Persistent link: https://www.econbiz.de/10005223036
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