# ================================================================================
# ================================= CORE METRICS =================================
# ================================================================================
===== FINAL SUMMARY =====
Best epoch : 1
Train accuracy : 0.762000
Val accuracy : 0.762667
Train loss : 0.162137
Val loss : 0.158374
Threshold : 0.570000
Test accuracy : 0.740000
Test loss : 0.571433 ===== TRAIN =====
Classification Report| precision | recall | f1-score | support | |
|---|---|---|---|---|
| 0 | 0.781282 | 0.955224 | 0.859541 | 2412.000000 |
| 1 | 0.803993 | 0.407169 | 0.540574 | 1088.000000 |
| accuracy | 0.784857 | 0.784857 | 0.784857 | 3500.000000 |
| macro avg | 0.792637 | 0.681196 | 0.700057 | 3500.000000 |
| weighted avg | 0.788342 | 0.784857 | 0.760388 | 3500.000000 |
| Positive (1) | Negative (0) | |
|---|---|---|
| Positive (1) | 443 | 108 |
| Negative (0) | 645 | 2304 |
AUC/AUPRC AUC (ROC): 0.833371 AUPRC: 0.721644
===== VALIDATION =====
Classification Report| precision | recall | f1-score | support | |
|---|---|---|---|---|
| 0 | 0.742188 | 0.969388 | 0.840708 | 490.000000 |
| 1 | 0.863636 | 0.365385 | 0.513514 | 260.000000 |
| accuracy | 0.760000 | 0.760000 | 0.760000 | 750.000000 |
| macro avg | 0.802912 | 0.667386 | 0.677111 | 750.000000 |
| weighted avg | 0.784290 | 0.760000 | 0.727281 | 750.000000 |
| Positive (1) | Negative (0) | |
|---|---|---|
| Positive (1) | 95 | 15 |
| Negative (0) | 165 | 475 |
AUC/AUPRC AUC (ROC): 0.856888 AUPRC: 0.767956
===== TEST =====
Classification Report| precision | recall | f1-score | support | |
|---|---|---|---|---|
| 0 | 0.780031 | 0.943396 | 0.853971 | 530.000000 |
| 1 | 0.724771 | 0.359091 | 0.480243 | 220.000000 |
| accuracy | 0.772000 | 0.772000 | 0.772000 | 750.000000 |
| macro avg | 0.752401 | 0.651244 | 0.667107 | 750.000000 |
| weighted avg | 0.763821 | 0.772000 | 0.744344 | 750.000000 |
| Positive (1) | Negative (0) | |
|---|---|---|
| Positive (1) | 79 | 30 |
| Negative (0) | 141 | 500 |
AUC/AUPRC AUC (ROC): 0.801844 AUPRC: 0.644767
Scenario D emits three structured log tables that document ensemble behavior and make the MAIN vs TEMP workflow auditable and reproducible.
Main Log (main_log) —
Iteration-level snapshots of the Primary (MAIN) ensemble state and
evaluation results under the selected metric.
Movement Log (movement_log) —
Deterministic promotion and replacement events between TEMP and MAIN
(what moved, directionality, and why).
Change Log (change_log) —
Per-iteration update diagnostics and structural deltas recorded during
training and selection steps.
These tables are returned in res_D$runs[[1]]$tables.
The previews below are capped for vignette readability.
| serial | iteration | phase | metric_name | metric_value | message | timestamp |
|---|---|---|---|---|---|---|
| 0.0.1 | 1 | main_before | accuracy | 0.5386667 | 2026-02-24 09:50:38 | |
| 0.0.2 | 1 | main_before | accuracy | 0.6933333 | 2026-02-24 09:50:38 | |
| 0.0.1 | 1 | main_after | accuracy | 0.6693333 | 2026-02-24 09:50:45 | |
| 0.0.2 | 1 | main_after | accuracy | 0.8160000 | 2026-02-24 09:50:45 | |
| 0.0.1 | 2 | main_before | accuracy | 0.6693333 | 2026-02-24 09:50:45 | |
| 0.0.2 | 2 | main_before | accuracy | 0.8160000 | 2026-02-24 09:50:45 | |
| 0.0.1 | 2 | main_after | accuracy | 0.6693333 | 2026-02-24 09:50:52 | |
| 0.0.2 | 2 | main_after | accuracy | 0.8160000 | 2026-02-24 09:50:52 |
| serial | iteration | message | timestamp |
|---|---|---|---|
| 0.0.1 | 1 | removed (no replacement) | 2026-02-24 09:50:45 |
| 0.0.1 | 2 | removed (no replacement) | 2026-02-24 09:50:52 |
| serial | iteration | message | timestamp |
|---|---|---|---|
| 0.0.1 | 1 | model removed from main | 2026-02-24 09:50:45 |
| 0.0.1 | 2 | model removed from main | 2026-02-24 09:50:52 |
Note: Tables below are preview-capped for vignette
readability. Full tables remain available in res_D\(runs[[1]]\)tables. Artifact writing
is OFF by default for CRAN-safety.