21in7 24f0faa540 fix(mlx): remove double normalization in walk-forward validation ...

Add normalize=False parameter to MLXFilter.fit() so external callers
can skip internal normalization. Remove the external normalization +
manual _mean/_std reset hack from walk_forward_auc() in train_mlx_model.py.

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

2026-03-21 18:31:11 +09:00

..

__init__.py

feat: implement ML filter with LightGBM for trading signal validation

2026-03-01 17:07:18 +09:00

collect_oi.py

feat: add OI long-term collection script for cron-based data accumulation

2026-03-04 20:24:14 +09:00

compare_symbols.py

feat: add symbol comparison and position sizing analysis tools

2026-03-18 23:35:42 +09:00

deploy_model.sh

feat: add --symbol/--all CLI to all training scripts for per-symbol pipeline

2026-03-05 23:21:32 +09:00

fetch_history.py

fix: add retry with exponential backoff to OI/funding API calls (#4)

2026-03-07 16:00:52 +09:00

position_sizing_analysis.py

feat: add symbol comparison and position sizing analysis tools

2026-03-18 23:35:42 +09:00

profile_training.py

feat: remove in-container retraining, training is now mac-only

2026-03-01 18:54:00 +09:00

run_backtest.py

feat: strategy parameter sweep and production param optimization

2026-03-06 23:39:43 +09:00

run_optuna.sh

feat: add run_optuna.sh wrapper script for Optuna tuning

2026-03-02 14:50:50 +09:00

run_tests.sh

feat: implement HOLD negative sampling and stratified undersampling in ML pipeline

2026-03-03 00:13:42 +09:00

strategy_sweep.py

feat: strategy parameter sweep and production param optimization

2026-03-06 23:39:43 +09:00

test_reverse_reenter.sh

feat: implement immediate re-entry after closing position on reverse signal

2026-03-02 01:34:36 +09:00

train_and_deploy.sh

feat: enhance data handling and model training features

2026-03-05 23:57:44 +09:00

train_mlx_model.py

fix(mlx): remove double normalization in walk-forward validation

2026-03-21 18:31:11 +09:00

train_model.py

fix(ml): pass SL/TP multipliers to dataset generation — align train/serve

2026-03-21 18:16:50 +09:00

tune_hyperparams.py

fix(ml): pass SL/TP multipliers to dataset generation — align train/serve

2026-03-21 18:16:50 +09:00

weekly_report.py

feat(weekly-report): add kill switch monitoring section

2026-03-18 23:58:22 +09:00