Resumen de Classification Error of the Thresholded Independence Rule.

Britta Anker Bak, Jens L. Jensen, Morten Fenger-Grøn

• 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 that is taylored to a mean value of interest in biological applications.