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- techniques used to adjust imbalances in the class distribution or ratio between categories in a data set (en)
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- Model Comparison and Calibration Assessment User Guide for Consistent Scoring Functions in Machine Learning and Actuarial Practice, Tobias Fissler, arXiv:2202.12780v3, Christian Lorentzen, Michael Mayer, 2023 (en)
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- Poor models in [the binary classification] setting are often a result of—any combination of—fitting deterministic classifiers, using re-sampling or re-weighting methods to balance class frequencies in the training data and evaluating the model with a score such as accuracy. ... No re-sampling technique will magically generate more information out of the few cases with the rare class. (en)
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- Oversampling and undersampling in data analysis (en)
- 오버샘플링과 언더샘플링 (ko)
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