__________ test_estimator_get_response_values[False-estimator2-score] __________
[gw1] darwin -- Python 3.13.11 /Users/runner/miniconda3/envs/testvenv/bin/python

estimator = KMeans(n_clusters=2, n_init=1), response_method = 'score'
return_response_method_used = False

    @pytest.mark.parametrize(
        "estimator, response_method",
        [
            (LinearRegression(), "predict"),
            (KMeans(n_clusters=2, n_init=1), "predict"),
            (KMeans(n_clusters=2, n_init=1), "score"),
            (KMeans(n_clusters=2, n_init=1), ["predict", "score"]),
            (IsolationForest(random_state=0), "predict"),
            (IsolationForest(random_state=0), "decision_function"),
            (IsolationForest(random_state=0), ["decision_function", "predict"]),
        ],
    )
    @pytest.mark.parametrize("return_response_method_used", [True, False])
    def test_estimator_get_response_values(
        estimator, response_method, return_response_method_used
    ):
        """Check the behaviour of `_get_response_values`."""
        X, y = np.random.RandomState(0).randn(10, 2), np.array([0, 1] * 5)
        estimator.fit(X, y)
        results = _get_response_values(
            estimator,
            X,
            response_method=response_method,
            return_response_method_used=return_response_method_used,
        )
        chosen_response_method = (
            response_method[0] if isinstance(response_method, list) else response_method
        )
        prediction_method = getattr(estimator, chosen_response_method)
>       assert_array_equal(results[0], prediction_method(X))
E       AssertionError: 
E       Arrays are not equal
E       
E       Mismatched elements: 1 / 1 (100%)
E       Max absolute difference among violations: 8.8817842e-16
E       Max relative difference among violations: 1.36774746e-16
E        ACTUAL: array(-6.493731)
E        DESIRED: array(-6.493731)

X          = array([[ 1.76405235,  0.40015721],
       [ 0.97873798,  2.2408932 ],
       [ 1.86755799, -0.97727788],
       [ 0.95... 0.12167502],
       [ 0.44386323,  0.33367433],
       [ 1.49407907, -0.20515826],
       [ 0.3130677 , -0.85409574]])
chosen_response_method = 'score'
estimator  = KMeans(n_clusters=2, n_init=1)
prediction_method = <bound method _BaseKMeans.score of KMeans(n_clusters=2, n_init=1)>
response_method = 'score'
results    = (-6.493731071053089, None)
return_response_method_used = False
y          = array([0, 1, 0, 1, 0, 1, 0, 1, 0, 1])

../sklearn/utils/tests/test_response.py:81: AssertionError