backup: 2026-08-29 06:59

thesisexperiments.org

@@ -5,20 +5,91 @@
 #+title: thesis/experiments
 #+filetags: :project: :knowledge: :experiments:
 
-:PROPERTIES:
-:ID: thesis-experiments
-:END:
+Chapter 4 of the BGU MSc thesis on ROLL. Parent: [[id:6294e2be-6189-4473-b363-a1dd9a75ff9b][thesis]]
 
-#+title: thesis/experiments
-#+filetags: :project: :knowledge: :experiments:
+** Data Sources
 
-Chapter 4 of the BGU MSc thesis on ROLL. Not yet written.
-Parent: [[id:6294e2be-6189-4473-b363-a1dd9a75fb9b][thesis]]
+- =results-final/keel/= — 12 KEEL datasets × 8 methods × 5 episodes, clean labels
+- =results-final/keel-noise-05/10/20/= — same 12 datasets × 8 methods × 10 episodes, asymmetric noise
+- =results-final/cifar10n/= — 3 noise levels (clean/aggre/worse) × 7 methods × 3 episodes; no roll-tpr90
+- =results-final/bank-marketing/=, =creditcard/=, =homecredit/= — 5 episodes each, all methods
+- =results-final/chestxray14/= — 5 episodes × 7 methods (libauc missing due to bug); image dataset
 
-** Guidelines
+** ChestXray14 Setup (IMPORTANT)
 
-- Target length: 15–20 pages
-- Datasets: KEEL imbalanced benchmark suite + larger datasets TBD
-- Baselines should include: cross-entropy + class weighting, AUC-surrogate methods, NP-inspired methods
-- Primary metric: TPR at fixed FPR; secondary: partial AUC, comparison across operating points
-- Report results for all three ROLL instantiations (Gaussian, Beta, KDE) to justify the progression
+- Dataset: NIH ChestX-ray14 (~112K frontal X-rays, 30,805 patients)
+- Task: Effusion (pleural effusion) vs. rest; IR ~7.5:1, ~12% prevalence
+- Label noise: ~20% organic — labels from NLP extraction of radiology reports (NOT injected)
+- Feature extraction: DenseNet-121 pretrained on NIH via TorchXRayVision (=densenet121-res224-nih=)
+  - Frozen; global avg pool of penultimate feature map → 1024-dim embeddings
+  - Script: =scripts/extract_chestxray14_features.py=
+- Classifier: 1024→512→128→1 MLP with Dropout(0.3)
+- n=5 episodes; LibAUC excluded (PESG optimizer instability on this task)
+- Experiment: =experiments/other/experiment-chestxray14.py=
+
+** Key Results
+
+*** ChestXray14 (primary new result — real-world organic noise)
+| Method   | AUC   | Std   |
+|----------|-------|-------|
+| roll-aoc | 0.839 | 0.001 | ← BEST, clear win
+| gce-0.7  | 0.829 | 0.004 |
+| roll-tpr | 0.828 | 0.002 |
+| mae      | 0.810 | 0.001 |
+| focal    | 0.798 | 0.009 |
+| bce-w    | 0.788 | 0.008 |
+| asym.    | 0.729 | 0.007 |
+| libauc   | ---   |       |
+
+*** KEEL Noise Experiment (primary thesis result)
+Mean AUC across all 12 KEEL datasets at increasing asymmetric label-noise rates:
+
+| Method    | 0%    | 5%    | 10%   | 20%   | Drop 0→20 |
+|-----------|-------|-------|-------|-------|-----------|
+| roll-aoc  | 0.880 | 0.871 | 0.862 | 0.847 | −0.033    |
+| bce-w     | 0.872 | 0.869 | 0.862 | 0.843 | −0.029    |
+| focal     | 0.879 | 0.868 | 0.857 | 0.842 | −0.037    |
+| asym.     | 0.892 | 0.872 | 0.870 | 0.833 | −0.059    |
+| gce-0.7   | 0.886 | 0.870 | 0.865 | 0.831 | −0.056    |
+| libauc    | 0.882 | 0.859 | 0.854 | 0.809 | −0.073    |
+| mae       | 0.875 | 0.878 | 0.866 | 0.804 | −0.071    |
+| roll-tpr  | 0.843 | 0.786 | 0.771 | 0.773 | −0.070    |
+
+*ROLL-AOC is best at 20% noise* despite being mid-pack at 0%. GCE/MAE degrade most.
+
+*** CIFAR-10N (image noise)
+| Noise  | roll-aoc | gce   | mae   | libauc | bce   | focal | asym  |
+|--------|----------|-------|-------|--------|-------|-------|-------|
+| clean  | 0.980    | 0.976 | 0.976 | 0.979  | 0.977 | 0.977 | 0.972 |
+| aggre  | 0.934    | 0.932 | 0.930 | 0.921  | 0.924 | 0.912 | 0.910 |
+| worse  | 0.821    | 0.774 | 0.809 | 0.752  | 0.738 | 0.734 | 0.720 |
+
+*** Large Datasets
+- Credit Card Fraud: roll-tpr90 best (0.974), roll-aoc close (0.968)
+- Home Credit: roll-aoc best (0.712), libauc very close (0.711)
+- Bank Marketing: ROLL FAILS — roll-aoc 0.511, roll-tpr90 0.438; GCE best (0.746). Open question.
+
+** Gotchas
+
+- "Label-noise experiment" is NOT a poisoning attack — it's asymmetric noise injection (flip pos→neg)
+- keel-noise runs use 10 episodes; clean keel uses 5
+- libauc-auroc missing 2 episodes for glass2 in clean KEEL (n=58 not 60)
+- cifar10n has no roll-tpr90 variant; table excludes it
+- chestxray14 libauc missing entirely — PESG optimizer instability; needs rerun
+- Bank Marketing failure cause unknown
+
+** Section Structure
+
+| Section | Label | Status |
+|---------|-------|--------|
+| Datasets (incl. ChestXray14) | sec:experiments:data_sets | Done |
+| Performance Measures | sec:experiments:performance_measures | Done |
+| Configurations | sec:experiments:configurations | Done |
+| KEEL Results | sec:results:keel | Done |
+| CIFAR-10N Results | sec:results:cifar10n | Done |
+| Large Datasets Results | sec:results:large | Done |
+| ChestXray14 Results | sec:results:chestxray14 | Done |
+| Label-Noise Robustness on KEEL | sec:experiments:noise | Done |
+| Ablation Study | sec:experiments:ablation | Stub |
+| Sensitivity Analysis | sec:experiments:sensitivity | Stub |
+| Summary | sec:experiments:summary | TODO |