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SUMMARY A Bayesian approach is made to the problem of using individuals of unconfirmed categories to provide information supplementary to a basic data bank of categorized observations. The exact analysis is briefly presented, followed by suggestions for more practicable approximate procedures, which are applied to examples involving medical and simulated data. The general conclusion is that the discriminatory performance of the data bank can be usefully improved by making use of uncategorized observations.
D. M. Titterington (Thu,) studied this question.
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