F*: an interpretable transformation of the F-measure
Date
2021
Authors
Hand, David
Christen, Peter
Kirielle, Nishadi
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Volume Title
Publisher
Kluwer Academic Publishers
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.
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Keywords
F1-score, Classifcation, Interpretability, Performance, Error rate, Precision, Recall
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Source
Machine Learning
Type
Journal article
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Open Access
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Creative Commons Attribution 4.0 International License
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