Journal
PATTERN RECOGNITION LETTERS
Volume 167, Issue -, Pages 115-121Publisher
ELSEVIER
DOI: 10.1016/j.patrec.2023.02.005
Keywords
Soft measures; Evaluation; Precision; Recall; F-score
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Precision and recall, classical measures in machine learning, are based on exact matching. However, in pattern recognition, inexact matching is often preferred. To address this issue, soft variants of precision and recall are introduced, based on application-specific similarity measures.
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.
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