chore: update active LGBM parameters and add new training log entry

- Updated timestamp and elapsed seconds in models/active_lgbm_params.json.
- Adjusted baseline AUC and fold AUCs to reflect new model performance.
- Added a new entry in models/training_log.json with detailed metrics from the latest training run, including tuned parameters and model path.

Made-with: Cursor

models/active_lgbm_params.json

@@ -1,17 +1,17 @@
 {
-  "timestamp": "2026-03-02T14:47:49.965976",
+  "timestamp": "2026-03-02T15:01:10.464634",
   "data_path": "data/combined_15m.parquet",
   "n_trials_total": 50,
   "n_trials_complete": 44,
-  "elapsed_sec": 70.8,
+  "elapsed_sec": 71.3,
   "baseline": {
-    "auc": 0.580343,
+    "auc": 0.579164,
     "fold_aucs": [
-      0.657825,
-      0.568182,
-      0.456471,
-      0.548148,
-      0.671088
+      0.689655,
+      0.540909,
+      0.484706,
+      0.533333,
+      0.647215
     ]
   },
   "best_trial": {

models/training_log.json

@@ -276,5 +276,30 @@
     "features": 23,
     "time_weight_decay": 2.0,
     "model_path": "models/lgbm_filter.pkl"
+  },
+  {
+    "date": "2026-03-02T14:51:09.101738",
+    "backend": "lgbm",
+    "auc": 0.5361,
+    "best_threshold": 0.5308,
+    "best_precision": 0.406,
+    "best_recall": 0.371,
+    "samples": 533,
+    "features": 23,
+    "time_weight_decay": 2.0,
+    "model_path": "models/lgbm_filter.pkl",
+    "tuned_params_path": "models/tune_results_20260302_144749.json",
+    "lgbm_params": {
+      "n_estimators": 434,
+      "learning_rate": 0.123659,
+      "num_leaves": 14,
+      "min_child_samples": 10,
+      "subsample": 0.929062,
+      "colsample_bytree": 0.94633,
+      "reg_alpha": 0.573971,
+      "reg_lambda": 0.000157,
+      "max_depth": 6
+    },
+    "weight_scale": 1.783105
   }
 ]