feat: adjust Random Forest parameters for improved model performance

app/training/train_classifier.py

@@ -254,9 +254,9 @@ def _build_candidates() -> list[tuple[str, Any]]:
             "Random Forest",
             RandomForestClassifier(
                 n_estimators=200,
-                max_depth=12,
-                min_samples_leaf=8,
-                min_samples_split=10,
+                max_depth=8,
+                min_samples_leaf=15,
+                min_samples_split=20,
                 class_weight="balanced",
                 random_state=42,
                 n_jobs=-1,