feat: Add XGBoost ML Signal Quality Predictor

Browse Source

- New ml_signal_predictor.py with XGBoost model
- Feature extraction from historical trades (17 features)
- 5-fold cross-validation for robust training
- Integrated into enhanced_trading_check_wrapper as optional layer
- Disabled by default until model improves (AUC: 0.508)
- Key insight: Asian session is strongest predictor of success

Features used:
- Signal: confidence, threshold, regime_strength
- Session: asian/london/ny/overlap (one-hot)
- Time: hour (cyclical), day_of_week
- Quality: signal_quality score
- Direction: long/short

Usage:
- train_ml_model() to train
- enable_ml_predictor() to activate
- get_ml_status() for info

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

...

This commit is contained in:

cbazza

2026-02-02 10:37:32 +01:00

co-authored by Claude Opus 4.5

parent 4ac27cc7b4

commit 7f2de4d227

4 changed files with 990 additions and 2106 deletions

Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL

Download Patch File Download Diff File Expand all files Collapse all files

TradingBot_V1.6_Adaptive_Complete_CORRECTED.ipynb

+166 -2106

File diff suppressed because it is too large Load Diff