96 lines
4.3 KiB
Org Mode
96 lines
4.3 KiB
Org Mode
:PROPERTIES:
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:ID: 59f84838-71a9-4aab-a494-8e6bae2080fb
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:END:
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#+title: thesis/experiments
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#+filetags: :project: :knowledge: :experiments:
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Chapter 4 of the BGU MSc thesis on ROLL. Parent: [[id:6294e2be-6189-4473-b363-a1dd9a75ff9b][thesis]]
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** Data Sources
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- =results-final/keel/= — 12 KEEL datasets × 8 methods × 5 episodes, clean labels
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- =results-final/keel-noise-05/10/20/= — same 12 datasets × 8 methods × 10 episodes, asymmetric noise
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- =results-final/cifar10n/= — 3 noise levels (clean/aggre/worse) × 7 methods × 3 episodes; no roll-tpr90
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- =results-final/bank-marketing/=, =creditcard/=, =homecredit/= — 5 episodes each, all methods
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- =results-final/chestxray14/= — 5 episodes × 7 methods (libauc missing due to bug); image dataset
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** ChestXray14 Setup (IMPORTANT)
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- Dataset: NIH ChestX-ray14 (~112K frontal X-rays, 30,805 patients)
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- Task: Effusion (pleural effusion) vs. rest; IR ~7.5:1, ~12% prevalence
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- Label noise: ~20% organic — labels from NLP extraction of radiology reports (NOT injected)
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- Feature extraction: DenseNet-121 pretrained on NIH via TorchXRayVision (=densenet121-res224-nih=)
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- Frozen; global avg pool of penultimate feature map → 1024-dim embeddings
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- Script: =scripts/extract_chestxray14_features.py=
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- Classifier: 1024→512→128→1 MLP with Dropout(0.3)
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- n=5 episodes; LibAUC excluded (PESG optimizer instability on this task)
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- Experiment: =experiments/other/experiment-chestxray14.py=
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** Key Results
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*** ChestXray14 (primary new result — real-world organic noise)
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| Method | AUC | Std |
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|----------|-------|-------|
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| roll-aoc | 0.839 | 0.001 | ← BEST, clear win
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| gce-0.7 | 0.829 | 0.004 |
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| roll-tpr | 0.828 | 0.002 |
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| mae | 0.810 | 0.001 |
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| focal | 0.798 | 0.009 |
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| bce-w | 0.788 | 0.008 |
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| asym. | 0.729 | 0.007 |
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| libauc | --- | |
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*** KEEL Noise Experiment (primary thesis result)
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Mean AUC across all 12 KEEL datasets at increasing asymmetric label-noise rates:
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| Method | 0% | 5% | 10% | 20% | Drop 0→20 |
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|-----------|-------|-------|-------|-------|-----------|
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| roll-aoc | 0.880 | 0.871 | 0.862 | 0.847 | −0.033 |
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| bce-w | 0.872 | 0.869 | 0.862 | 0.843 | −0.029 |
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| focal | 0.879 | 0.868 | 0.857 | 0.842 | −0.037 |
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| asym. | 0.892 | 0.872 | 0.870 | 0.833 | −0.059 |
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| gce-0.7 | 0.886 | 0.870 | 0.865 | 0.831 | −0.056 |
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| libauc | 0.882 | 0.859 | 0.854 | 0.809 | −0.073 |
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| mae | 0.875 | 0.878 | 0.866 | 0.804 | −0.071 |
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| roll-tpr | 0.843 | 0.786 | 0.771 | 0.773 | −0.070 |
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*ROLL-AOC is best at 20% noise* despite being mid-pack at 0%. GCE/MAE degrade most.
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*** CIFAR-10N (image noise)
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| Noise | roll-aoc | gce | mae | libauc | bce | focal | asym |
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|--------|----------|-------|-------|--------|-------|-------|-------|
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| clean | 0.980 | 0.976 | 0.976 | 0.979 | 0.977 | 0.977 | 0.972 |
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| aggre | 0.934 | 0.932 | 0.930 | 0.921 | 0.924 | 0.912 | 0.910 |
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| worse | 0.821 | 0.774 | 0.809 | 0.752 | 0.738 | 0.734 | 0.720 |
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*** Large Datasets
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- Credit Card Fraud: roll-tpr90 best (0.974), roll-aoc close (0.968)
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- Home Credit: roll-aoc best (0.712), libauc very close (0.711)
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- Bank Marketing: ROLL FAILS — roll-aoc 0.511, roll-tpr90 0.438; GCE best (0.746). Open question.
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** Gotchas
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- "Label-noise experiment" is NOT a poisoning attack — it's asymmetric noise injection (flip pos→neg)
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- keel-noise runs use 10 episodes; clean keel uses 5
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- libauc-auroc missing 2 episodes for glass2 in clean KEEL (n=58 not 60)
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- cifar10n has no roll-tpr90 variant; table excludes it
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- chestxray14 libauc missing entirely — PESG optimizer instability; needs rerun
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- Bank Marketing failure cause unknown
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** Section Structure
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| Section | Label | Status |
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|---------|-------|--------|
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| Datasets (incl. ChestXray14) | sec:experiments:data_sets | Done |
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| Performance Measures | sec:experiments:performance_measures | Done |
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| Configurations | sec:experiments:configurations | Done |
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| KEEL Results | sec:results:keel | Done |
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| CIFAR-10N Results | sec:results:cifar10n | Done |
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| Large Datasets Results | sec:results:large | Done |
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| ChestXray14 Results | sec:results:chestxray14 | Done |
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| Label-Noise Robustness on KEEL | sec:experiments:noise | Done |
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| Ablation Study | sec:experiments:ablation | Stub |
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| Sensitivity Analysis | sec:experiments:sensitivity | Stub |
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| Summary | sec:experiments:summary | TODO |
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