fix sklearn warning (#2442)

* fix sklearn warning

* lint

deepchecks/tabular/metric_utils/scorers.py

@@ -17,6 +17,8 @@
 
 import numpy as np
 import pandas as pd
+from packaging import version
+from sklearn import __version__ as scikit_version
 from sklearn.base import ClassifierMixin
 from sklearn.metrics import get_scorer, log_loss, make_scorer, mean_absolute_error, mean_squared_error
 from sklearn.metrics._scorer import _BaseScorer, _ProbaScorer
@@ -442,7 +444,9 @@ def _transform_to_multi_label_format(y: np.ndarray, classes):
     # Some classifiers like catboost might return shape like (n_rows, 1), therefore squeezing the array.
     y = np.squeeze(y) if y.ndim > 1 else y
     if y.ndim == 1:
-        ohe = OneHotEncoder(handle_unknown='ignore', sparse=False)
+        kwargs = {'sparse_output': False} if version.parse(scikit_version) >= version.parse('1.2') \
+            else {'sparse': False}
+        ohe = OneHotEncoder(handle_unknown='ignore', **kwargs)  # pylint: disable=unexpected-keyword-arg
         ohe.fit(np.array(classes).reshape(-1, 1))
         return ohe.transform(y.reshape(-1, 1))
     # If after squeeze there are still 2 dimensions, then it must have column for each model class.