Definition
Assume an information retrieval (IR) system has recall R and precision P on a test document collection and an information need. The F-measure of the system is defined as the weighted harmonic mean of its precision and recall, that is, \( F=\frac{1}{\alpha \frac{1}{P}+\left(1-\alpha \right)\frac{1}{R}} \), where the weight α ∈ [0,1]. The balanced F-measure, commonly denoted as F 1 or just F, equally weighs precision and recall, which means α = 1∕2. The F 1 measure can be written as \( {F}_1=\frac{2PR}{P+R} \).
Key Points
The F-measure can be viewed as a compromise between recall and precision. It is high only when both recall and precision are high. It is equivalent to recall when α = 0 and precision when α = 1. The F-measure assumes values in the interval [0,1]. It is 0 when no relevant documents have been retrieved, and is 1 if all retrieved documents are relevant and all relevant documents have been retrieved.
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© 2016 Springer Science+Business Media New York
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Zhang, E., Zhang, Y. (2016). F-Measure. In: Liu, L., Özsu, M. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4899-7993-3_483-2
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DOI: https://doi.org/10.1007/978-1-4899-7993-3_483-2
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