Medical researchers have solved the problem of estimating the sensitivity and specificity of binary medical diagnostic tests without gold standard tests for comparison. That problem is the same as estimating confusion matrices for classifiers on unlabeled data. This article describes how to modify the diagnostic test solutions to estimate confusion matrices and accuracy statistics for supervised or unsupervised binary classifiers on unlabeled data.

翻译：医学研究人员已经解决了估算二进制医学诊断测试的敏感性和特殊性的问题,而没有进行黄金标准测试以进行比较,这个问题与估算分类人员在无标签数据上的混乱矩阵相同,该条描述了如何修改诊断测试解决方案,以估算无标签数据上受监督或无人监督的二进制分类人员的混乱矩阵和准确性统计数据。