TST FIX binary y in sample weight equivalence check (scikit-learn#30775)

Author: antoinebaker

doc/whats_new/upcoming_changes/sklearn.utils/30775.fix.rst

@@ -0,0 +1,5 @@
+-  In :mod:`utils.estimator_checks` we now enforce for binary classifiers a
+   binary `y` by taking the minimum as the negative class instead of the first
+   element, which makes it robust to `y` shuffling. It prevents two checks from
+   wrongly failing on binary classifiers.
+   By :user:`Antoine Baker <antoinebaker>`.

sklearn/utils/estimator_checks.py

@@ -3934,7 +3934,7 @@ def _enforce_estimator_tags_y(estimator, y):
         and not tags.classifier_tags.multi_class
         and y.size > 0
     ):
-        y = np.where(y == y.flat[0], y, y.flat[0] + 1)
+        y = np.where(y == y.min(), y, y.min() + 1)
     # Estimators in mono_output_task_error raise ValueError if y is of 1-D
     # Convert into a 2-D y for those estimators.
     if tags.target_tags.multi_output and not tags.target_tags.single_output: