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

Subrata Kundu and Adam T. Martinsek

Statistics & Probability Letters, 1998, vol. 37, issue 1, 19-27

Abstract: 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.

Keywords: Classification; Discrimination; Pattern; recognition; Density; estimate; Stopping; rule (search for similar items in EconPapers)
Date: 1998
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