benchUpdated

Signed-off-by: giandos200 <[email protected]>

Author: giandos200

docs/source/notebooks/Benchmarking_different_CF_explanation_methods.ipynb

@@ -274,7 +274,7 @@
     "    for q in query_instances:\n",
     "        if q in d.categorical_feature_names:\n",
     "            query_instances.loc[:, q] = \\\n",
-    "                [random.choice(dataset[q].unique()) for _ in query_instances.index]\n",
+    "                [random.choice(dataset[q].values.unique()) for _ in query_instances.index]\n",
     "        else:\n",
     "            query_instances.loc[:, q] = \\\n",
     "                [np.random.uniform(dataset[q].min(), dataset[q].max()) for _ in query_instances.index]\n",
@@ -329,4 +329,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 5
-}
+}

tests/test_dice_interface/test_explainer_base.py

@@ -181,8 +181,8 @@ def test_global_feature_importance_error_conditions_with_insufficient_cfs_per_qu
         with pytest.raises(
             UserConfigValidationException,
             match="The number of counterfactuals generated per query instance should be "
-                    "greater than or equal to 10 "
-                    "to compute global feature importance over all query points"):
+                  "greater than or equal to 10 "
+                  "to compute global feature importance over all query points"):
             exp.global_feature_importance(
                 query_instances=None,
                 cf_examples_list=cf_explanations.cf_examples_list)