标记性
度量(数据仓库)
召回
统计的
相关性
计算机科学
自然语言处理
人工智能
统计
心理学
数学
认知心理学
语言学
数据挖掘
哲学
几何学
出处
期刊:Cornell University - arXiv
日期:2020-01-01
被引量:729
标识
DOI:10.48550/arxiv.2010.16061
摘要
Commonly used evaluation measures including Recall, Precision, F-Measure and Rand Accuracy are biased and should not be used without clear understanding of the biases, and corresponding identification of chance or base case levels of the statistic. Using these measures a system that performs worse in the objective sense of Informedness, can appear to perform better under any of these commonly used measures. We discuss several concepts and measures that reflect the probability that prediction is informed versus chance. Informedness and introduce Markedness as a dual measure for the probability that prediction is marked versus chance. Finally we demonstrate elegant connections between the concepts of Informedness, Markedness, Correlation and Significance as well as their intuitive relationships with Recall and Precision, and outline the extension from the dichotomous case to the general multi-class case.
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