fix(qav3): handle xgboost sklearn API properly

Signed-off-by: Jérôme Benoit <jerome.benoit@piment-noir.org>

diff --git a/quickadapter/user_data/strategies/Utils.py b/quickadapter/user_data/strategies/Utils.py
index 69101e39ae5c458ae0ed41854551bf9efbb98152..a73216b602164b9c84d8b04a945e2da8c8a8e68a 100644 (file)
--- a/quickadapter/user_data/strategies/Utils.py
+++ b/quickadapter/user_data/strategies/Utils.py
@@ -743,12 +743,12 @@ def fit_regressor(
     init_model: Any = None,
     callbacks: Optional[list[Callable]] = None,
 ) -> Any:
-    if model_training_parameters.get("seed") is None:
-        model_training_parameters["seed"] = 1
-
     if regressor == "xgboost":
         from xgboost import XGBRegressor
 
+        if model_training_parameters.get("random_state") is None:
+            model_training_parameters["random_state"] = 1
+
         model = XGBRegressor(
             objective="reg:squarederror",
             eval_metric="rmse",
@@ -766,6 +766,9 @@ def fit_regressor(
     elif regressor == "lightgbm":
         from lightgbm import LGBMRegressor
 
+        if model_training_parameters.get("seed") is None:
+            model_training_parameters["seed"] = 1
+
         model = LGBMRegressor(objective="regression", **model_training_parameters)
         model.fit(
             X=X,