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Existing techniques that automatically derive a classifier from a set of labelled objects try to minimize the error rate. Diagnostic classifiers used in medicine, however, are often intended to be optimal for other performance measures, such as sensitivity and specificity. We developed an algorithm that induces decision rules which fulfil user-specified performance requirements. Basically, the algorithm...
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