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Simplify README focus on methodology
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README.md
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@@ -38,7 +38,6 @@ A production-ready **Self-Normalizing Neural Network (SNN) ensemble** for predic
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| **Activation** | SELU + AlphaDropout |
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| **Training** | 300 epochs, 40-fold CV |
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| **CV AUC** | 0.882 ± 0.021 |
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| **Test AUC** | 0.990 (MoleculeNet scaffold split) |
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## Molecular Features (11,369 total)
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- **Normalization**: SquashScaler (StandardScaler → tanh → StandardScaler)
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- **Ensemble Selection**: Top-10 folds from 40-fold stratified CV
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## Performance (MoleculeNet Test Split)
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| Endpoint | AUC | Samples | Positives |
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| NR-AR | 0.998 | 703 | 30 |
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| NR-AR-LBD | 0.998 | 618 | 20 |
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| NR-AhR | 0.985 | 601 | 85 |
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| NR-Aromatase | 0.992 | 496 | 45 |
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| NR-ER | 0.963 | 546 | 81 |
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| NR-ER-LBD | 0.996 | 657 | 31 |
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| NR-PPAR-gamma | 0.998 | 562 | 32 |
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| SR-ARE | 0.977 | 466 | 104 |
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| SR-ATAD5 | 0.998 | 651 | 28 |
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| SR-HSE | 0.992 | 564 | 43 |
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| SR-MMP | 0.993 | 512 | 108 |
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| SR-p53 | 0.991 | 624 | 72 |
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| **Mean** | **0.990** | - | - |
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## Tox21 Endpoints
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### Nuclear Receptor Panel
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| **Activation** | SELU + AlphaDropout |
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| **Training** | 300 epochs, 40-fold CV |
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| **CV AUC** | 0.882 ± 0.021 |
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## Molecular Features (11,369 total)
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- **Normalization**: SquashScaler (StandardScaler → tanh → StandardScaler)
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- **Ensemble Selection**: Top-10 folds from 40-fold stratified CV
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## Tox21 Endpoints
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### Nuclear Receptor Panel
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