Abstract
The classification problem consists of assigning subjects to one of several available treatments on the basis of their test scores, where the success of each treatment is measured by a different criterion. It is indicated how this problem can be formulated as an (empirical) Bayes decision problem. As an example, the case of classification with a threshold utility function is analyzed, and optimal assignment rules are derived. The results are illustrated empirically with data from a classification problem in which achievement test data are used to assign students to appropriate continuation schools.
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