An Empirical Bayes Approach to Non-Parametric Two-Way Classification

摘要

The report considers the problem of classifying an individual into one of two categories in the non-parametric case. Classification procedures are proposed which make use of all observations previously taken on individuals independently selected from the same population. These procedures have risks which are asymptotically optimum as the number of prior observations becomes large. The loss due to misclassification is assumed to depend on the value of a random variable associated with the individual but not observed at the time of classification. The case where only one of the losses due to misclassification of individuals previously selected from the population is known is also, considered, and similar results are obtained. (Author)