- 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
11 lines
92 B
Plaintext
11 lines
92 B
Plaintext
.env
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__pycache__/
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*.pyc
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.pytest_cache/
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logs/
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*.log
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.venv/
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venv/
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models/*.pkl
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data/*.parquet
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