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feat: update default LightGBM params to Optuna best (trial #46, AUC=0.6002)

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Optuna 50 trials Walk-Forward 5폴드 탐색 결과 (tune_results_20260302_144749.json):
- Baseline AUC: 0.5803 → Best AUC: 0.6002 (+0.0199, +3.4%)
- n_estimators: 500 → 434
- learning_rate: 0.05 → 0.123659
- max_depth: (미설정) → 6
- num_leaves: 31 → 14
- min_child_samples: 15 → 10
- subsample: 0.8 → 0.929062
- colsample_bytree: 0.8 → 0.946330
- reg_alpha: 0.05 → 0.573971
- reg_lambda: 0.1 → 0.000157
- weight_scale: 1.0 → 1.783105

Made-with: Cursor
This commit is contained in:
21in7
2026-03-02 14:52:41 +09:00
parent ce02f1335c
commit d5f8ed4789
1 changed files with 10 additions and 9 deletions
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19
scripts/train_model.py
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@@ -151,16 +151,17 @@ def _load_lgbm_params(tuned_params_path: str | None) -> tuple[dict, float]:
반환: (lgbm_params, weight_scale) 반환: (lgbm_params, weight_scale)
""" """
lgbm_params: dict = { lgbm_params: dict = {
"n_estimators": 500, "n_estimators": 434,
"learning_rate": 0.05, "learning_rate": 0.123659,
"num_leaves": 31, "max_depth": 6,
"min_child_samples": 15, "num_leaves": 14,
"subsample": 0.8, "min_child_samples": 10,
"colsample_bytree": 0.8, "subsample": 0.929062,
"reg_alpha": 0.05, "colsample_bytree": 0.946330,
"reg_lambda": 0.1, "reg_alpha": 0.573971,
"reg_lambda": 0.000157,
} }
weight_scale = 1.0 weight_scale = 1.783105
if tuned_params_path: if tuned_params_path:
with open(tuned_params_path, "r", encoding="utf-8") as f: with open(tuned_params_path, "r", encoding="utf-8") as f: