scikit-learn · jeremiedbb · Aug 8, 2025 · Aug 3, 2025 · Aug 3, 2025 · Aug 3, 2025
diff --git a/doc/whats_new/upcoming_changes/sklearn.utils/31873.enhancement.rst b/doc/whats_new/upcoming_changes/sklearn.utils/31873.enhancement.rst
@@ -0,0 +1,4 @@
+``sklearn.utils._check_sample_weight`` now raises a clearer error message when the
+provided weights are neither a scalar nor a 1-D array-like of the same size as the
+input data.
+:issue:`31712` by :user:`Kapil Parekh <kapslock123>`.
diff --git a/sklearn/utils/tests/test_validation.py b/sklearn/utils/tests/test_validation.py
@@ -1608,7 +1608,7 @@ def _check_sample_weight_common(xp):
     assert_allclose(_convert_to_numpy(sample_weight, xp), 2 * np.ones(5))
 
     # check wrong number of dimensions
-    with pytest.raises(ValueError, match="Sample weights must be 1D array or scalar"):
+    with pytest.raises(ValueError, match=r"Sample weights must be 1D array or scalar"):
         _check_sample_weight(xp.ones((2, 4)), X=xp.ones((2, 2)))
 
     # check incorrect n_samples

diff --git a/sklearn/utils/validation.py b/sklearn/utils/validation.py
@@ -2222,7 +2222,11 @@ def _check_sample_weight(
             input_name="sample_weight",
         )
         if sample_weight.ndim != 1:
-            raise ValueError("Sample weights must be 1D array or scalar")
+            raise ValueError(
+                f"Sample weights must be 1D array or scalar, got "
+                f"{sample_weight.ndim}D array. Expected either a scalar value "
+                f"or a 1D array of length {n_samples}."
+            )
 
         if sample_weight.shape != (n_samples,):
             raise ValueError(