Change default parameter of SVC model in the GCM module

Before, the Support Vector Classifier did not produce probabilities, which are required for different algorithms in the GCM module. This changes the 'probability' parameter to True.

Signed-off-by: Patrick Bloebaum <bloebp@amazon.com>

Author: bloebp

dowhy/gcm/ml/classification.py

@@ -76,7 +76,7 @@ def create_ada_boost_classifier(**kwargs) -> SklearnClassificationModel:
 
 
 def create_support_vector_classifier(**kwargs) -> SklearnClassificationModel:
-    return SklearnClassificationModel(SVC(**kwargs))
+    return SklearnClassificationModel(SVC(**kwargs, probability=True))
 
 
 def create_knn_classifier(**kwargs) -> SklearnClassificationModel:

tests/gcm/ml/test_classification.py

@@ -2,6 +2,7 @@
 from flaky import flaky
 
 from dowhy.gcm.ml import create_hist_gradient_boost_classifier, create_polynom_logistic_regression_classifier
+from dowhy.gcm.ml.classification import create_support_vector_classifier
 
 
 @flaky(max_runs=3)
@@ -58,3 +59,9 @@ def _generate_data():
     mdl.fit(X_training, Y_training)
 
     assert np.sum(mdl.predict(X_test).reshape(-1) == Y_test) > 950
+
+
+def test_given_svc_model_then_supports_predict_probabilities():
+    mdl = create_support_vector_classifier()
+    mdl.fit(np.random.normal(0, 1, 100), np.random.choice(2, 100).astype(str))
+    mdl.predict_probabilities(np.random.normal(0, 1, 10))