Table 5
Held-out test set performance with BCa bootstrap 95% CIs.
| Model | Accuracy (%) | Macro F1 (%) | MCC |
|---|---|---|---|
| XGBoost | 99.89 [99.63, 99.96] | 99.89 [99.70, 99.96] | 0.999 |
| RF | 99.85 [99.59, 99.93] | 99.85 [99.63, 99.96] | 0.998 |
| SoftCBM | 99.04 [98.56, 99.33] | 99.04 [98.61, 99.37] | 0.988 |
| HardCBM-Cal | 96.48 [95.67, 97.07] | 96.46 [95.73, 97.09] | 0.957 |
| CEM | 96.70 [95.93, 97.26] | 96.69 [95.98, 97.30] | 0.960 |
| MLP | 95.04 [94.15, 95.78] | 95.00 [94.18, 95.76] | 0.940 |
| HardCBM | 94.19 [93.22, 94.96] | 94.12 [93.22, 94.94] | 0.930 |
| HardCBM-Lin | 88.85 [87.59, 89.96] | 88.65 [87.46, 89.83] | 0.866 |
Notes. BCa bootstrap with 10 000 resamples. Brackets show 95% confidence intervals. The held-out predictions summarized in this table are drawn from models trained with the identical hyperparameters reported in Sect. 3.3; the small differences between cross-validation means in Table 4 and the bootstrap means here (e.g., HardCBM 94.41% vs. 94.19%) reflect the CV-versus-held-out test split, not model differences.
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