foxhunt

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jgrusewski c0c44a5f17 feat(dqn): GPU-native regime classification with 42-dim feature vector

Expand FeatureVector from 40 to 42 dimensions by including ADX(14) at
index 40 and CUSUM direction at index 41 from the existing CPU feature
extraction pipeline. This eliminates proxy-based regime classification
and enables GPU-native regime detection via tensor narrow/comparison ops.

Key changes:
- extraction.rs: wire RegimeADXFeatures + RegimeCUSUMFeatures into
  extract_current_features_v2(), output 42 features per bar
- regime_conditional.rs: classify_regime_masks_gpu() creates per-regime
  mask tensors entirely on GPU (ADX > 0.25 = trending, |CUSUM| > 0.7 =
  volatile, else ranging). Zero CPU roundtrip in training hot path.
- trainer.rs/config.rs: state_dim 43→45 (no OFI), 51→53 (with OFI),
  aligned dims unchanged (48/56). GPU batch insertion for all 3 heads.
- CUDA header: MARKET_DIM 40→42
- walk_forward.rs: FEATURE_DIM 40→42
- 42 files updated, all [f64;40]→[f64;42] propagated across workspace

Test results: ml=874/0, ml-dqn=354/0, ml-features=282/0, ml-core=274/0
Real data GPU smoke tests: 7/7 passed (OHLCV + OFI + trade enrichment)
Hyperopt baseline RL: 2 trials completed on local RTX 3050 Ti

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

2026-03-09 12:16:05 +01:00

baseline_common

fix(ml): wire spread_cost_bps into RL training — commission + spread = total tx cost

2026-03-01 22:10:43 +01:00

cuda_test.rs

chore: clean up examples, update ML binaries and risk tests

2026-02-27 01:33:18 +01:00

download_baseline.rs

feat(infra): training data cache architecture — MinIO → PVC sync

2026-03-07 14:45:30 +01:00

evaluate_baseline.rs

feat(ml): real trade data pipeline for VPIN/Kyle's Lambda + offline RL