F*: an interpretable transformation of the F-measure

被引:0
|
作者
David J. Hand
Peter Christen
Nishadi Kirielle
机构
[1] Imperial College London,School of Computer Science
[2] The Australian National University,undefined
来源
Machine Learning | 2021年 / 110卷
关键词
F1-score; Classification; Interpretability; Performance; Error rate; Precision; Recall;
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暂无
中图分类号
学科分类号
摘要
The F-measure, also known as the F1-score, is widely used to assess the performance of classification algorithms. However, some researchers find it lacking in intuitive interpretation, questioning the appropriateness of combining two aspects of performance as conceptually distinct as precision and recall, and also questioning whether the harmonic mean is the best way to combine them. To ease this concern, we describe a simple transformation of the F-measure, which we call F∗\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$F^*$$\end{document} (F-star), which has an immediate practical interpretation.
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收藏
页码:451 / 456
页数:5
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