cointrader

gihyeon/cointrader

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Author	SHA1	Message	Date
21in7	2b3f39b5d1	feat: enhance data handling and model training features - Updated .gitignore to include .venv and .worktrees. - Removed symlink for the virtual environment. - Added new parquet files for dogeusdt, trxusdt, and xrpusdt datasets. - Introduced model files and training logs for dogeusdt, trxusdt, and xrpusdt. - Enhanced fetch_history.py to support caching of correlation symbols. - Updated train_and_deploy.sh to manage correlation cache directory.	2026-03-05 23:57:44 +09:00
21in7	2bb2bf2896	feat: add per-symbol model/data directories and update .env.example Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-03-05 23:24:50 +09:00
21in7	7e4e9315c2	feat: implement ML filter with LightGBM for trading signal validation - Added MLFilter class to load and evaluate LightGBM model for trading signals. - Introduced retraining mechanism to update the model daily based on new data. - Created feature engineering and label building utilities for model training. - Updated bot logic to incorporate ML filter for signal validation. - Added scripts for data fetching and model training. Made-with: Cursor	2026-03-01 17:07:18 +09:00

Author

SHA1

Message

Date

21in7

2b3f39b5d1

feat: enhance data handling and model training features

- Updated .gitignore to include .venv and .worktrees.
- Removed symlink for the virtual environment.
- Added new parquet files for dogeusdt, trxusdt, and xrpusdt datasets.
- Introduced model files and training logs for dogeusdt, trxusdt, and xrpusdt.
- Enhanced fetch_history.py to support caching of correlation symbols.
- Updated train_and_deploy.sh to manage correlation cache directory.

2026-03-05 23:57:44 +09:00

21in7

2bb2bf2896

feat: add per-symbol model/data directories and update .env.example

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

2026-03-05 23:24:50 +09:00

21in7

7e4e9315c2

feat: implement ML filter with LightGBM for trading signal validation

- Added MLFilter class to load and evaluate LightGBM model for trading signals.
- Introduced retraining mechanism to update the model daily based on new data.
- Created feature engineering and label building utilities for model training.
- Updated bot logic to incorporate ML filter for signal validation.
- Added scripts for data fetching and model training.

Made-with: Cursor

2026-03-01 17:07:18 +09:00

3 Commits