- Fix LightGBM predict_proba ValueError by filtering FEATURE_COLS and casting to float64
- Extract BTC/ETH correlation data from embedded parquet columns instead of missing separate files
- Disable ONNX priority in ML filter tests to use mocked LightGBM correctly
- Add NO_ML_FILTER=true to .env.example (ML adds no value with current signal thresholds)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Added ML_THRESHOLD to .env.example and updated Config class to include ml_threshold with a default value of 0.55.
- Modified MLFilter initialization in bot.py to utilize the new ml_threshold configuration.
- Updated Jenkinsfile to change the registry URL for Docker image management.
These changes enhance the model's adaptability by allowing for a configurable machine learning threshold, improving overall performance.
