Sybil Attack Address Detection Demo Pipeline

Description

This is a machine learning demo example, convenient for beginners to learn and compete

Clone this repo. Install the dependencies from the requirements.txt file. If there are any other missing dependencies, please install them yourself.
Create the following folders
- ./data/
- ./saved_model/
- ./data/raw_data/
- ./data/features/
Place all the data files for the competition in the ./data/raw_data/ directory, included:
- train_dataset.parquet
- test_dataset.parquet
- transactions.parquet
- token_transfers.parquet
- dex_swaps.parquet
Run python feature_process.py to generate the feature file at ./data/features/transactions_feature.parquet.
Run python train.py to train and save model.
Run python inference.py to generate test dataset prediction result as pred.csv.
Submit the pred.csv file to the website to view the accuracy of the test set.