Improve error message for MeanShift.estimate_bandwidth when X is sparse scikit-learn#8627 (scikit-learn#8771)

* raise error on sparse matrix in estimate_bandwidth of mean_shift

* Remove added newline

Author: AishwaryaRK

sklearn/cluster/mean_shift_.py

@@ -62,6 +62,8 @@ def estimate_bandwidth(X, quantile=0.3, n_samples=None, random_state=0,
     bandwidth : float
         The bandwidth parameter.
     """
+    X = check_array(X)
+
     random_state = check_random_state(random_state)
     if n_samples is not None:
         idx = random_state.permutation(X.shape[0])[:n_samples]

sklearn/cluster/tests/test_mean_shift.py

@@ -6,6 +6,8 @@
 import numpy as np
 import warnings
 
+from scipy import sparse
+
 from sklearn.utils.testing import assert_equal
 from sklearn.utils.testing import assert_false
 from sklearn.utils.testing import assert_true
@@ -47,6 +49,13 @@ def test_mean_shift():
     assert_equal(n_clusters_, n_clusters)
 
 
+def test_estimate_bandwidth_with_sparse_matrix():
+    # Test estimate_bandwidth with sparse matrix
+    X = sparse.lil_matrix((1000, 1000))
+    msg = "A sparse matrix was passed, but dense data is required."
+    assert_raise_message(TypeError, msg, estimate_bandwidth, X, 200)
+
+
 def test_parallel():
     ms1 = MeanShift(n_jobs=2)
     ms1.fit(X)