From: Jérôme Benoit <jerome.benoit@piment-noir.org>
Date: Mon, 15 Sep 2025 19:03:17 +0000 (+0200)
Subject: fix(qav3): handle xgboost sklearn API properly
X-Git-Url: https://git.piment-noir.org/?a=commitdiff_plain;h=bbc5b4cfb5b1e40b2eefccd30a302bea53e53a7d;p=freqai-strategies.git

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 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,