Commit Graph

10 Commits

Author SHA1 Message Date
21in7
30ddb2fef4 feat(ml): relax training thresholds for 5-10x more training samples
Add TRAIN_* constants (signal_threshold=2, adx=15, vol_mult=1.5, neg_ratio=3)
as dataset_builder defaults. Remove hardcoded negative_ratio=5 from all callers.
Bot entry conditions unchanged (config.py strict values).

WF 5-fold results (all symbols AUC 0.91+):
- XRPUSDT: 0.9216 ± 0.0052
- SOLUSDT:  0.9174 ± 0.0063
- DOGEUSDT: 0.9222 ± 0.0085

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-21 19:38:15 +09:00
21in7
a34fc6f996 fix(mlx): use stratified_undersample consistent with LightGBM
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-21 18:33:36 +09:00
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
21in7
0cc5835b3a fix(ml): pass SL/TP multipliers to dataset generation — align train/serve
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-21 18:16:50 +09:00
21in7
0f6a22fcb5 feat: MLX 임계값 탐색을 정밀도 우선(recall>=0.15 조건부)으로 변경
Made-with: Cursor
2026-03-01 23:54:38 +09:00
21in7
3b7ee3e890 chore: .worktrees/ gitignore에 추가
Made-with: Cursor
2026-03-01 23:50:18 +09:00
21in7
4245d7cdbf feat: implement 15-minute timeframe upgrade for model training and data processing
- Introduced a new markdown document detailing the plan to transition the entire pipeline from a 1-minute to a 15-minute timeframe, aiming to improve model AUC from 0.49-0.50 to over 0.53.
- Updated key parameters across multiple scripts, including `LOOKAHEAD` adjustments and default data paths to reflect the new 15-minute interval.
- Modified data fetching and training scripts to ensure compatibility with the new timeframe, including changes in `fetch_history.py`, `train_model.py`, and `train_and_deploy.sh`.
- Enhanced the bot's data stream configuration to operate on a 15-minute interval, ensuring real-time data processing aligns with the new model training strategy.
- Updated training logs to capture new model performance metrics under the revised timeframe.
2026-03-01 22:16:15 +09:00
21in7
d9238afaf9 feat: enhance MLX model training with combined data handling
- Introduced a new function `_split_combined` to separate XRP, BTC, and ETH data from a combined DataFrame.
- Updated `train_mlx` to utilize the new function, improving data management and feature handling.
- Adjusted dataset generation to accommodate BTC and ETH features, with warnings for missing features.
- Changed default data path in `train_mlx` and `train_model` to point to the combined dataset for consistency.
- Increased `LOOKAHEAD` from 60 to 90 and adjusted `ATR_TP_MULT` for better model performance.
2026-03-01 21:43:27 +09:00
21in7
db144750a3 feat: enhance model training and deployment scripts with time-weighted sampling
- Updated `train_model.py` and `train_mlx_model.py` to include a time weight decay parameter for improved sample weighting during training.
- Modified dataset generation to incorporate sample weights based on time decay, enhancing model performance.
- Adjusted deployment scripts to support new backend options and improved error handling for model file transfers.
- Added new entries to the training log for better tracking of model performance metrics over time.
- Included ONNX model export functionality in the MLX filter for compatibility with Linux servers.
2026-03-01 21:25:06 +09:00
21in7
fd96055e73 perf: replace generate_dataset with vectorized version in train_mlx_model
Made-with: Cursor
2026-03-01 18:53:21 +09:00