foxhunt

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jgrusewski 4cff7a56a7 test(ml): add DQN training smoke test with 6 core assertions

Assertions verified on real 6E.FUT data:
1. All 20 epochs complete (no premature early stopping)
2. Loss decreases >5% (gradient flow works) — actual: 22.4%
3. All per-epoch losses are finite (no NaN/Inf)
4. Q-value divergence (model develops action preferences)
5. Checkpoint round-trip (save/load weight integrity)
6. Epsilon decayed below 0.5 (exploration schedule ran)

Also fixes divide-by-zero in triple_barrier.rs:103 when
entry_price_cents is zero (guard in both barrier tracker
and trainer caller).

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

2026-02-20 20:17:34 +01:00

meta_labeling

feat(wave12): Complete ML warning fixes and add Parquet training infrastructure

2025-10-21 08:54:26 +02:00

benchmarks.rs

fix(dqn): Wave D Production Readiness - 100% test pass rate

2025-11-05 02:21:58 +01:00

concurrent_tracking.rs

feat(wave-d): Complete Wave D Phase 6 with 240+ parallel agents

2025-10-19 09:10:55 +02:00

constants.rs

🔧 Emergency Fix: Resolve catastrophic _i32 suffix corruption (463→0 errors)