fix: LinearSVC results now reproducible (#1376)

Co-authored-by: Daniel Grindrod <Daniel.Grindrod@evotec.com>

flaml/automl/model.py

@@ -2185,6 +2185,11 @@ class SVCEstimator(SKLearnEstimator):
 
     def __init__(self, task="binary", **config):
         super().__init__(task, **config)
+        self.params.update(
+            {
+                "random_state": config.get("random_seed", 10242048),
+            }
+        )
         assert self._task.is_classification(), "LinearSVC for classification task only"
         self.estimator_class = LinearSVC
 

test/automl/test_classification.py

@@ -435,6 +435,7 @@ class TestClassification(unittest.TestCase):
         # "lrl1",
         "lrl2",
         "rf",
+        "svc",
         "xgboost",
         "xgb_limitdepth",
     ],
@@ -495,6 +496,7 @@ def test_reproducibility_of_classification_models(estimator: str):
         # "lgbm",
         # "lrl1",
         "lrl2",
+        "svc",
         "rf",
         "xgboost",
         "xgb_limitdepth",