rckrdmrd
75c4d07690
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>
258 lines
5.2 KiB
JSON
258 lines
5.2 KiB
JSON
{
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"features": [
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"open",
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"high",
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"low",
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"close",
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"volume",
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"ATR",
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"SAR",
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"RSI",
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"MFI",
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"OBV",
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"AD",
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"CMF",
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"volume_z",
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"volume_anomaly"
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],
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"symbols": [
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"XAUUSD",
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"EURUSD",
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"BTCUSD"
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],
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"timeframes": [
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"5m",
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"15m"
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],
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"results": {
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"XAUUSD_5m_high_h3": {
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"mae": 1.0452576341613162,
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"rmse": 1.47518779980032,
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"r2": -0.3217012243095463,
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"feature_columns": [
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"ATR",
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"SAR",
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"RSI",
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"MFI",
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"OBV",
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"AD",
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"CMF",
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"volume_z",
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"volume_anomaly"
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]
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},
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"XAUUSD_5m_low_h3": {
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"OBV",
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"AD",
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"CMF",
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"volume_z",
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"volume_anomaly"
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]
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},
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"XAUUSD_15m_high_h3": {
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"AD",
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"CMF",
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"volume_anomaly"
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]
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},
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"AD",
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"CMF",
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"volume_z",
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"volume_anomaly"
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]
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},
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"EURUSD_5m_high_h3": {
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"AD",
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"CMF",
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"volume_z",
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"volume_anomaly"
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"MFI",
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"OBV",
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"AD",
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"CMF",
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"volume_z",
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"volume_anomaly"
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]
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"OBV",
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"AD",
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"CMF",
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"volume_z",
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"AD",
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"CMF",
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"volume_z",
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"volume_anomaly"
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},
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"BTCUSD_5m_high_h3": {
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"AD",
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"CMF",
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}
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},
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"trained_at": "2026-01-05T02:48:25.475116"
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} |