| B-MO IRON ORE TRAINING SUMMARY |
| Deposits used: 975 Background points: 1950 Spatial blocks: 122 |
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| Model ranking (spatial CV, all points), best first: |
| 0.858 XGBoost [+terrain] finds 60% of deposits at 10% false alarms |
| 0.853 Gradient Boosting [+terrain] finds 59% of deposits at 10% false alarms |
| 0.853 Random Forest [+terrain] finds 59% of deposits at 10% false alarms |
| 0.852 Extra Trees [+terrain] finds 57% of deposits at 10% false alarms |
| 0.849 LightGBM [+terrain] finds 61% of deposits at 10% false alarms |
| 0.848 Logistic Regression [+terrain] finds 60% of deposits at 10% false alarms |
| 0.845 SVM (RBF) [+terrain] finds 61% of deposits at 10% false alarms |
| 0.840 k-Nearest Neighbours [+terrain] finds 57% of deposits at 10% false alarms |
| 0.828 Extra Trees [+thermal] finds 52% of deposits at 10% false alarms |
| 0.823 Random Forest [+thermal] finds 52% of deposits at 10% false alarms |
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| Statistical engine chosen: Statistical engine (likelihood variant), feature set '+terrain', AUC 0.782 |
| Average engine score -> known deposits: 55.4 background: 40.2 |
| Where deposits and background land (out-of-fold, %): |
| class deposits_pct background_pct |
| Very low 10.8 50.0 |
| Low 29.0 25.0 |
| Moderate 18.6 15.0 |
| High 18.2 7.0 |
| Very high 23.5 3.0 |
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| Top features: B8 (AUC 0.22), brightness (AUC 0.25), B11 (AUC 0.26), slope (AUC 0.73), B3 (AUC 0.29), B12 (AUC 0.30) |
| Hyperspectral: evaluated on the small covered subset - see model_comparison.csv |
