scikit-learn
diff --git a/‎sklearn/linear_model/tests/test_coordinate_descent.py
Copy file name to clipboardExpand all lines: sklearn/linear_model/tests/test_coordinate_descent.py
+9Lines changed: 9 additions & 0 deletions b/‎sklearn/linear_model/tests/test_coordinate_descent.py
Copy file name to clipboardExpand all lines: sklearn/linear_model/tests/test_coordinate_descent.py
+9Lines changed: 9 additions & 0 deletions
@@ -1369,9 +1369,18 @@ def test_enet_cv_sample_weight_correctness(
     )
     reg_with_repetitions.fit(X_with_repetitions, y_with_repetitions)
 
+    # Check that the alpha selection process is the same:
     assert_allclose(reg_with_weights.mse_path_, reg_with_repetitions.mse_path_)
     assert_allclose(reg_with_weights.alphas_, reg_with_repetitions.alphas_)
     assert reg_with_weights.alpha_ == pytest.approx(reg_with_repetitions.alpha_)
+
+    # Ensure that the models selected a non-boundary alpha to make sure that
+    # the sample_weight equivalence test is non-degenerate.
+    alphas = reg_with_weights.alphas_
+    alpha = reg_with_weights.alpha_
+    assert alphas[0] > alpha > alphas[-1]
+
+    # Check that the final model coefficients are the same:
     assert_allclose(reg_with_weights.coef_, reg_with_repetitions.coef_, atol=1e-10)
     assert reg_with_weights.intercept_ == pytest.approx(reg_with_repetitions.intercept_)