⚠️ CI failed on Linux_Runs.pylatest_conda_forge_mkl (last failure: Apr 26, 2025) ⚠️

**CI failed on [Linux_Runs.pylatest_conda_forge_mkl](https://dev.azure.com/scikit-learn/scikit-learn/_build/results?buildId=75987&view=logs&j=dde5042c-7464-5d47-9507-31bdd2ee0a3a)** (Apr 26, 2025)
- test_precomputed_nearest_neighbors_filtering[60]

COMMENT:
For the record, the failure was the following:

```python
_______________ test_precomputed_nearest_neighbors_filtering[60] _______________
[gw0] linux -- Python 3.13.3 /usr/share/miniconda/envs/testvenv/bin/python

global_random_seed = 60

    def test_precomputed_nearest_neighbors_filtering(global_random_seed):
        # Test precomputed graph filtering when containing too many neighbors
        X, y = make_blobs(
            n_samples=250,
            random_state=global_random_seed,
            centers=[[1, 1], [-1, -1]],
            cluster_std=0.01,
        )
    
        n_neighbors = 2
        results = []
        for additional_neighbors in [0, 10]:
            nn = NearestNeighbors(n_neighbors=n_neighbors + additional_neighbors).fit(X)
            graph = nn.kneighbors_graph(X, mode="connectivity")
            labels = (
                SpectralClustering(
                    random_state=global_random_seed,
                    n_clusters=2,
                    affinity="precomputed_nearest_neighbors",
                    n_neighbors=n_neighbors,
                )
                .fit(graph)
                .labels_
            )
            results.append(labels)
    
>       assert_array_equal(results[0], results[1])
E       AssertionError: 
E       Arrays are not equal
E       
E       Mismatched elements: 139 / 250 (55.6%)
E       Max absolute difference among violations: 1
E       Max relative difference among violations: 1.
E        ACTUAL: array([1, 1, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 1, 0, 1,
E              0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1,
E              1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1,...
E        DESIRED: array([1, 0, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 1, 1, 1,
E              0, 0, 0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0,
E              0, 1, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1,...

X          = array([[ 0.98723448,  0.9898586 ],
       [-1.00258762, -1.00697942],
       [ 0.98726373,  0.99184863],
       [ 0.98... 0.9927963 ],
       [-1.0010091 , -1.00391894],
       [ 1.01668103,  1.01155459],
       [-1.00678887, -0.99002748]])
additional_neighbors = 10
global_random_seed = 60
graph      = <Compressed Sparse Row sparse matrix of dtype 'float64'
	with 3000 stored elements and shape (250, 250)>
labels     = array([1, 0, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 1, 1, 1,
       0, 0, 0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 0,...,
       0, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1,
       0, 1, 0, 0, 1, 1, 1, 0], dtype=int32)
n_neighbors = 2
nn         = NearestNeighbors(n_neighbors=12)
results    = [array([1, 1, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 1, 0, 1,
       0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 1...
       0, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1,
       0, 1, 0, 0, 1, 1, 1, 0], dtype=int32)]
y          = array([0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0,
       0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1,...1, 1, 0, 0, 0,
       1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0,
       1, 0, 0, 0, 0, 1, 0, 1])

../1/s/sklearn/cluster/tests/test_spectral.py:130: AssertionError
```

Labels: module:test-suite