Updates for scikit-learn 1.4

Signed-off-by: Beat Buesser <[email protected]>

Author: beat-buesser

tests/attacks/evasion/test_lowprofool.py

@@ -329,7 +329,7 @@ def pearson_correlations(x, y):
         return result
 
     # Setup classifier
-    lr_clf = LogisticRegression(penalty=None)
+    lr_clf = LogisticRegression(penalty="l2")
     lr_clf.fit(x_train, y_train)
     clf_slr = ScikitlearnLogisticRegression(model=lr_clf, clip_values=clip_values)
 
@@ -392,7 +392,7 @@ def test_clipping(iris_dataset):
     (x_train, y_train, x_valid, y_valid), _, clip_values = iris_dataset
 
     # Setup classifier
-    lr_clf = LogisticRegression(penalty=None)
+    lr_clf = LogisticRegression(penalty="l2")
     lr_clf.fit(x_train, y_train)
 
     # Dataset min-max clipping values

tests/utils.py

@@ -1748,7 +1748,6 @@ def get_tabular_classifier_scikit_list(clipped=False, model_list_names=None):
     )
 
     sklearn_version = list(map(int, sklearn.__version__.split(".")))
-    sklearn_ge_1_3_0 = sklearn_version[0] == 1 and sklearn_version[1] == 3
     if sklearn_version[0] == 1 and sklearn_version[1] == 3:
         suffix = "-eq-1.3.0"
     elif sklearn_version[0] == 1 and sklearn_version[1] == 4: