F*: an interpretable transformation of the F-measure
File(s)
Author(s)
Hand, David
Christen, Peter
Kirielle, Nishadi
Type
Journal Article
Abstract
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∗ (F-star), which has an immediate practical interpretation.
Date Issued
2021-03-15
Date Acceptance
2020-11-05
Citation
Machine Learning, 2021, 110 (3), pp.451-456
URI
URL
DOI
ISSN
0885-6125
Publisher
Springer Verlag
Start Page
451
End Page
456
Journal / Book Title
Machine Learning
Volume
110
Issue
3
Copyright Statement
© 2021 Springer-Verlag. The final publication is available at Springer via https://doi.org/10.1007/s10994-021-05964-1. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
License URL
Identifier
https://link.springer.com/article/10.1007/s10994-021-05964-1
Subjects
Classification
Error rate
F1-score
Interpretability
Performance
Precision
Recall
0801 Artificial Intelligence and Image Processing
0806 Information Systems
1702 Cognitive Sciences
Artificial Intelligence & Image Processing
Publication Status
Published
Date Publish Online
2021-03-15