jgrusewski 8d5af977f7 feat: train_fold_from_slices — trainer accepts contiguous feature/target slices ...

Adds DQNTrainer::train_fold_from_slices(&[[f64;42]], &[[f64;4]]) so the
fold loop in train_baseline_rl passes raw fxcache slices directly, without
the caller constructing any Vec<(FeatureVector, Vec<f64>)>. Removes
features_to_trainer_format_fast helper (no longer needed) and updates
train_dqn_fold to call the new method.

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

2026-04-02 22:50:11 +02:00

..

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

fix: wire real GPU backprop + SPSA gradients, fix checkpoint loading, eliminate candle from examples

2026-03-20 15:41:42 +01:00

download_baseline.rs

fix: add retry with backoff to Databento download_quarter

2026-03-31 22:57:43 +02:00

evaluate_baseline.rs

feat: DQN gems — spectral decoupling, manifold mixup, regime replay, family hyperopt

2026-03-31 00:39:23 +02:00

evaluate_supervised.rs

fix: wire real GPU backprop + SPSA gradients, fix checkpoint loading, eliminate candle from examples

2026-03-20 15:41:42 +01:00

hyperopt_baseline_rl.rs

feat: configurable --min-hold-bars for A/B testing (3 vs 5)

2026-03-31 11:12:13 +02:00

hyperopt_baseline_supervised.rs

fix(clippy): resolve all clippy warnings across entire workspace (--all-targets)

2026-03-13 10:18:35 +01:00

precompute_features.rs

feat: fxcache stores per-bar timestamps for walk-forward windowing

2026-04-01 19:29:41 +02:00

train_baseline_rl.rs

feat: train_fold_from_slices — trainer accepts contiguous feature/target slices

2026-04-02 22:50:11 +02:00

train_baseline_supervised.rs

refactor: remove max_training_steps_per_epoch — always train full dataset

2026-04-02 14:41:16 +02:00