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A Comparative Approach to Threshold Optimization for ...
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由 J Hancock 著作2022被引用 14 次 — In this study we use four popular metrics to optimize thresholds: precision, Matthews' Correlation Coefficient, f-measure and geometric mean of true positive ...
A Comparative Approach to Threshold Optimization for ...
IEEE Computer Society
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由 J Hancock 著作2022被引用 14 次 — Our contribution is to present a systematic method for selecting the best threshold value for a given classification task and its desired performance ...
A Comparative Approach to Threshold Optimization for ...
Semantic Scholar
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Semantic Scholar
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This contribution is to present a systematic method for selecting the best threshold value for a given classification task and its desired performance ...
A Comparative Approach to Threshold Optimization for ...
ResearchGate
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ResearchGate
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... In a comparative study, Hancock et al. (2022) investigated several threshold optimization techniques for imbalanced datasets, including the use of metrics ...
A Comparative Approach to Threshold Optimization for ...
IEEE Computer Society
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IEEE Computer Society
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由 J Hancock 著作2022被引用 14 次 — In our literature review of studies involving selecting thresholds to optimize classification of imbalanced data, we find there is an opportunity to expand on.
A Comparative Approach to Threshold Optimization for ...
IEEE Computer Society
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2023年6月13日 — Voice over slide presentation of the research paper "A Comparative Approach to Threshold Optimization for Classifying Imbalanced Data"
Threshold optimization and random undersampling for ...
SpringerOpen
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SpringerOpen
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由 JL Leevy 著作2023被引用 28 次 — For comparative purposes, the default threshold of 0.5 is also investigated to determine whether it is suitable for classifying imbalanced data.
Threshold Moving Approaches for Addressing the Class ...
ACM Digital Library
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由 X Zhang 著作2020被引用 23 次 — In this paper, simple threshold moving techniques are proposed for the class imbalance problem. Decision thresholds are adjusted to match the class ...
Threshold optimization for classification in imbalanced data ...
ResearchGate
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We introduce a method to minimize the mean square error (MSE) of an estimator which is derived from a classification. The method chooses an optimal ...
Threshold optimization for classification in imbalanced data in ...
ACM Digital Library
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ACM Digital Library
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We introduce a method to minimize the mean square error (MSE) of an estimator which is derived from a classification. The method chooses an optimal ...