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FIX seed in test_ridge_sample_weight_consistency [all random seeds] #26589

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Merged
merged 2 commits into from
Jun 16, 2023
Merged

FIX seed in test_ridge_sample_weight_consistency [all random seeds] #26589

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edf3d9d
Fix seed in test_ridge_sample_weight_consistency [all random seeds]
ogrisel Jun 15, 2023
9f29b3b
Update sklearn/linear_model/tests/test_ridge.py
ogrisel Jun 16, 2023
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8 changes: 7 additions & 1 deletion sklearn/linear_model/tests/test_ridge.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1978,7 +1978,9 @@ def test_lbfgs_solver_error():
@pytest.mark.parametrize("sparseX", [False, True])
@pytest.mark.parametrize("data", ["tall", "wide"])
@pytest.mark.parametrize("solver", SOLVERS + ["lbfgs"])
def test_ridge_sample_weight_consistency(fit_intercept, sparseX, data, solver):
def test_ridge_sample_weight_consistency(
fit_intercept, sparseX, data, solver, global_random_seed
):
"""Test that the impact of sample_weight is consistent.

Note that this test is stricter than the common test
Expand All @@ -1989,6 +1991,9 @@ def test_ridge_sample_weight_consistency(fit_intercept, sparseX, data, solver):
if solver == "svd" or (solver in ("cholesky", "saga") and fit_intercept):
pytest.skip("unsupported configuration")

# XXX: this test is quite sensitive to the seed used to generate the data:
# ideally we would like the test to pass for any global_random_seed but this is not
# the case at the moment.
rng = np.random.RandomState(42)
n_samples = 12
if data == "tall":
Expand All @@ -2005,6 +2010,7 @@ def test_ridge_sample_weight_consistency(fit_intercept, sparseX, data, solver):
alpha=1.0,
solver=solver,
positive=(solver == "lbfgs"),
random_state=global_random_seed, # for sag/saga
tol=1e-12,
)

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