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Soft precision and recall
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DOI：10.1016/j.patrec.2023.02.005.png)
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Abstract
En 中文
Precision and recall are classical measures used in machine learning. However, they are based on exact matching. This results in binary classification where the predicted item is either a true or false positive despite inexact matching is often preferred in pattern recognition. To address this problem, we introduce soft variants of precision and recall based on application-specific similarity measure. 2022 Elsevier Ltd. All rights reserved.
Keywords:
Soft measures
Evaluation
Precision
Recall
F-score
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