Scripts: - Update ingest_ohlcv_polygon.py for improved data processing Reports: - Add attention model training reports (2x) - Add standard training reports (2x) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Hierarchical ML Pipeline for trading predictions: - Level 0: Attention Models (volatility/flow classification) - Level 1: Base Models (XGBoost per symbol/timeframe) - Level 2: Metamodels (XGBoost Stacking + Neural Gating) Key components: - src/pipelines/hierarchical_pipeline.py - Main prediction pipeline - src/models/ - All ML model classes - src/training/ - Training utilities - src/api/ - FastAPI endpoints - scripts/ - Training and evaluation scripts - config/ - YAML configurations Note: Trained models (*.joblib, *.pt) are gitignored. Regenerate with training scripts. Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
