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README.md
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Applying NAM model to manipulate monotonicity
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Applying Both on-chain data and off-chain data to train the model
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## Results
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| [main_dataset_processing_code.ipynb](https://huggingface.co/datasets/dkublockchain/FinML_Chain/blob/main/code/main_dataset_processing_code.ipynb) | Applying FinBert to process discord information; Applying the NAM model to manipulate monotonicity; Applying Both on-chain data and off-chain data to train the model
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| [NAM models.py](https://huggingface.co/datasets/dkublockchain/FinML_Chain/blob/main/code/NAM_models.py) | NAM model
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| [baseline_dataset_processing_code.ipynb](https://huggingface.co/datasets/dkublockchain/FinML_Chain/blob/main/code/baseline_dataset_processing_code.ipynb) | Using linear algorithm, DNN, XGBoost and long-short term memory to predict gas used.
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## Results
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