rckrdmrd 75c4d07690 feat: Initial commit - ML Engine codebase ... 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>		2026-01-18 04:27:40 -06:00
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TRAINING_REPORT_20260106_231824.md	feat: Initial commit - ML Engine codebase	2026-01-18 04:27:40 -06:00