diff --git a/onnxmltools/convert/xgboost/operator_converters/XGBoost.py b/onnxmltools/convert/xgboost/operator_converters/XGBoost.py
index 519d94ce..a9f31211 100644
--- a/onnxmltools/convert/xgboost/operator_converters/XGBoost.py
+++ b/onnxmltools/convert/xgboost/operator_converters/XGBoost.py
@@ -264,8 +264,8 @@ def convert(scope, operator, container):
         )
 
         if objective == "count:poisson":
-            cst = scope.get_unique_variable_name("half")
-            container.add_initializer(cst, TensorProto.FLOAT, [1], [0.5])
+            cst = scope.get_unique_variable_name("poisson")
+            container.add_initializer(cst, TensorProto.FLOAT, [1], [base_score])
             new_name = scope.get_unique_variable_name("exp")
             container.add_node("Exp", names, [new_name])
             container.add_node("Mul", [new_name, cst], operator.output_full_names)
diff --git a/tests/xgboost/test_xgboost_converters.py b/tests/xgboost/test_xgboost_converters.py
index 475d5b2a..7a37dd3a 100644
--- a/tests/xgboost/test_xgboost_converters.py
+++ b/tests/xgboost/test_xgboost_converters.py
@@ -94,12 +94,12 @@ def test_xgb_regressor_poisson(self):
         x = iris.data
         y = iris.target / 100
         x_train, x_test, y_train, _ = train_test_split(
-            x, y, test_size=0.5, random_state=42
+            x, y, test_size=0.5, random_state=17
         )
         for nest in [5, 50]:
             xgb = XGBRegressor(
                 objective="count:poisson",
-                random_state=0,
+                random_state=5,
                 max_depth=3,
                 n_estimators=nest,
             )
@@ -716,5 +716,4 @@ def test_xgb_classifier_13(self):
 
 
 if __name__ == "__main__":
-    TestXGBoostModels().test_xgb_regressor_poisson()
     unittest.main(verbosity=2)