On two imbalanced financial benchmarks, group-specific decision thresholds outperform or match SMOTE and CT-GAN augmentation across seven model families.
IEEE Transactions on Knowledge and Data Engineering21(9), 1263–1284 (Sep 2009)
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Beyond Synthetic Augmentation: Group-Aware Threshold Calibration for Robust Balanced Accuracy in Imbalanced Learning
On two imbalanced financial benchmarks, group-specific decision thresholds outperform or match SMOTE and CT-GAN augmentation across seven model families.