Calculating a boundary for the significance from the equal-error rate

机译：从等错误率计算重要性的边界

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Given a common dataset, two methods operating on that dataset and reported equal-error rate (EER) for each method, then we can estimate whether the two methods differ significantly at the threshold leading to the EER. This enables the calculation of a boundary on the significance for methods where the significance was not reported in the original paper or to compare new methods to older ones by evaluating them on the same dataset.

机译：给定一个公共数据集，在该数据集上操作两种方法并为每种方法报告均等错误率（EER），则我们可以估计这两种方法在导致EER的阈值处是否显着不同。这样就可以计算出在原始论文中未报告重要性的方法的重要性边界，或通过在同一数据集上对新方法与旧方法进行比较来将其与旧方法进行比较。

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来源
《2016 International Conference on Biometrics》|2016年|1-4|共4页
会议地点 Halmstad(SE)
作者
Heinz Hofbauer; Andreas Uhl;
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作者单位

University of Salzburg, Department of Computer Sciences, Austria;

University of Salzburg, Department of Computer Sciences, Austria;

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会议组织
原文格式 PDF
正文语种 eng
中图分类
关键词
Databases; Estimation; Iris recognition; Computers; Partitioning algorithms; Data mining; Error analysis;

机译：数据库;估计;虹膜识别;计算机;分区算法;数据挖掘;错误分析;

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Calculating a boundary for the significance from the equal-error rate

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