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README.md
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@@ -21,10 +21,12 @@ The ReTiNA dataset is available at this [Hugging Face Repository](https://huggin
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## 🤖 Available Models
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| Model | Architecture | Overall RMSE (s) | Overall MAE (s) | Overall R<sup>2</sup> |
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| ReTiNA_XGB1 | XGBoost | 182.81 | 119.30 | 0.659 |
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| ReTiNA_MLP1 | PyTorch Residual MLP | 202.67 | 141.79 | 0.516 |
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All models were evaluated across rigorous scaffold, cluster, and method splits.
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## 🤖 Available Models
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In retention time prediction, we recommend using ReTiNA_XGB1, as it has the highest overall prediction accuracy.
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| Model | Architecture | Overall RMSE (s) | Overall MAE (s) | Overall R<sup>2</sup> |
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| **ReTiNA_XGB1** | XGBoost | 182.81 | 119.30 | 0.659 |
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| **ReTiNA_MLP1** | PyTorch Residual MLP | 202.67 | 141.79 | 0.516 |
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All models were evaluated across rigorous scaffold, cluster, and method splits.
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