概率逻辑
计算机科学
精确性和召回率
召回
点估计
口译(哲学)
点(几何)
置信区间
人工智能
统计
数据挖掘
机器学习
数学
认知心理学
心理学
几何学
程序设计语言
作者
Cyril Goutte,Éric Gaussier
标识
DOI:10.1007/978-3-540-31865-1_25
摘要
We address the problems of 1/ assessing the confidence of the standard point estimates, precision, recall and F-score, and 2/ comparing the results, in terms of precision, recall and F-score, obtained using two different methods. To do so, we use a probabilistic setting which allows us to obtain posterior distributions on these performance indicators, rather than point estimates. This framework is applied to the case where different methods are run on different datasets from the same source, as well as the standard situation where competing results are obtained on the same data.
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