reduced n_samples and n_features in test_nan_support for faster pytest
@@ -115,7 +115,7 @@ def test_nan_support():
# Make sure nans are OK if the underlying estimator supports nans
rng = np.random.RandomState(0)
- n_samples, n_features = 100, 10
+ n_samples, n_features = 40, 4
X, y = make_regression(n_samples, n_features, random_state=0)
nan_mask = rng.randint(0, 2, size=(n_samples, n_features), dtype=bool)
X[nan_mask] = np.nan
