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Classification error of the thresholded independence rule

By Britta Anker Bak, Morten Fenger-Grøn and Jens Ledet Jensen
Thiele Research Reports
No. 05, December 2012
Abstract:
We consider classification in the situation of two groups with normally distributed data in the 'large $p$ small $n$' framework. To counterbalance the high number of variables we consider the thresholded independence rule. An upper bound on the classification error is established which is taylored to a mean value of interest in biological applications.
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