Tests: Add tests using the conjugate gradient optimizer

andreArtelt · Jul 16, 2019 · 83d1f74 · 83d1f74
1 parent 185a959
commit 83d1f74
Showing 1 changed file with 4 additions and 0 deletions.
diff --git a/tests/sklearn/test_sklearn_softmaxregression.py b/tests/sklearn/test_sklearn_softmaxregression.py
@@ -33,6 +33,10 @@ def test_softmaxregression():
     assert y_cf == 0
     assert model.predict(np.array([x_cf])) == 0
 
+    x_cf, y_cf, delta = generate_counterfactual(model, x_orig, 0, features_whitelist=features_whitelist, regularization="l1", C=1.0, optimizer="cg", return_as_dict=False)
+    assert y_cf == 0
+    assert model.predict(np.array([x_cf])) == 0
+
     x_cf, y_cf, delta = generate_counterfactual(model, x_orig, 0, features_whitelist=features_whitelist, regularization="l1", C=1.0, optimizer="nelder-mead", return_as_dict=False)
     assert y_cf == 0
     assert model.predict(np.array([x_cf])) == 0