From bbc5b4cfb5b1e40b2eefccd30a302bea53e53a7d Mon Sep 17 00:00:00 2001 From: =?utf8?q?J=C3=A9r=C3=B4me=20Benoit?= Date: Mon, 15 Sep 2025 21:03:17 +0200 Subject: [PATCH] fix(qav3): handle xgboost sklearn API properly MIME-Version: 1.0 Content-Type: text/plain; charset=utf8 Content-Transfer-Encoding: 8bit Signed-off-by: Jérôme Benoit --- quickadapter/user_data/strategies/Utils.py | 9 ++++++--- 1 file changed, 6 insertions(+), 3 deletions(-) diff --git a/quickadapter/user_data/strategies/Utils.py b/quickadapter/user_data/strategies/Utils.py index 69101e3..a73216b 100644 --- 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, -- 2.43.0