jgrusewski b09ebfc3cb feat(ml): add HyperparameterOptimizable trainers for all 8 supervised models ...

Extend hyperopt infrastructure to support all 10 ML models (DQN, PPO +
8 supervised). Previously only TFT and Mamba2 had hyperopt trainers.

- Add HyperparameterOptimizable impl for Liquid, TGGN, TLOB, KAN, xLSTM, Diffusion
- Create shared_data.rs with common data prep utilities (build_flat_pairs,
  build_sequence_pairs, write_trial_result_json)
- Extend hyperopt_baseline_supervised binary to dispatch all 8 models
  (individual, "both" for tft+mamba2, "all" for all 8)
- Add CI jobs: 7 train-validate + 10 hyperopt jobs for all models
- Fix DiffusionMetrics NaN default, XLSTMMetrics serde, safe indexing

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

2026-02-26 23:47:52 +01:00

..

baseline_common

fix(ml,ci): zero-dim guards on all 10 models, eliminate warnings, unblock CI parallelism

2026-02-26 17:38:43 +01:00

cuda_test.rs

refactor: restructure repo — crates/, bin/, testing/ layout

2026-02-25 11:56:00 +01:00

download_baseline.rs

refactor: delete 22 dead examples, 4 CSVs, consolidate data to test_data/

2026-02-26 01:24:02 +01:00

evaluate_baseline.rs

refactor: delete 22 dead examples, 4 CSVs, consolidate data to test_data/

2026-02-26 01:24:02 +01:00

evaluate_supervised.rs

fix(ml): correct checkpoint path in evaluate_supervised + persist NormStats

2026-02-26 22:49:44 +01:00

hyperopt_baseline_rl.rs

refactor: delete 22 dead examples, 4 CSVs, consolidate data to test_data/

2026-02-26 01:24:02 +01:00

hyperopt_baseline_supervised.rs

feat(ml): add HyperparameterOptimizable trainers for all 8 supervised models

2026-02-26 23:47:52 +01:00

train_baseline_rl.rs

feat: on-demand training dispatch via K8s Jobs with sidecar uploader

2026-02-26 12:43:17 +01:00

train_baseline_supervised.rs

fix(ml): correct checkpoint path in evaluate_supervised + persist NormStats

2026-02-26 22:49:44 +01:00