3 Commits

Author	SHA1	Message	Date
jgrusewski	afd85b2f8f	chore: clean up examples, update ML binaries and risk tests ... - Delete 14 unused example files (-3,543 lines): config, adaptive-strategy, data, storage, trading_engine, api_gateway, backtesting, trading_service, chaos - Update ML training/eval binaries: improved CLI args, completion tracking, CUDA test cleanup, hyperopt enhancements - Fix KAN network and TFT module adjustments - Update risk test assertions for consistency - Fix backtesting repositories and promotion manager - Update .serena project config and Cargo dependencies Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-02-27 01:33:18 +01:00
jgrusewski	b2086f74e6	fix(ml): correct checkpoint path in evaluate_supervised + persist NormStats ... evaluate_supervised looked for checkpoints at {models_dir}/{model}_fold{N}_best but training saves to {models_dir}/{model}/{model}_fold{N}_best (model subdirectory). Also saves NormStats JSON per fold during training so evaluation uses training-time normalization instead of computing from test data (data leakage). Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-02-26 22:49:44 +01:00
jgrusewski	0c1fe12645	feat(ml): add evaluate_supervised binary + PPO eval in CI ... New evaluate_supervised binary runs walk-forward inference on supervised model checkpoints (TFT, Mamba2, etc.), converts directional predictions to trading signals, and computes Sharpe/MaxDD/WinRate/DirAccuracy. CI changes: - train-validate-dqn → train-validate-rl (trains+evals DQN+PPO) - train-validate-tft now runs evaluate_supervised after training - web/api fallback rules added to train-validate and deploy stages - evaluate_supervised added to compile-services and Docker images Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-02-26 21:31:45 +01:00