Add bias analyzer for tabular data

omnixai/explainers/tabular/agnostic/bias.py

@@ -213,8 +213,8 @@ def rd(stats, pred_a, pred_b, labels):
         """
         Recall difference.
         """
-        return {label: stats[label]["tpa"] / stats[label]["na"] -
-                       stats[label]["tpb"] / stats[label]["nb"]
+        return {label: stats[label]["tpa"] / max(stats[label]["na"], 1) -
+                       stats[label]["tpb"] / max(stats[label]["nb"], 1)
                 for label in labels}
 
     @staticmethod

omnixai/tests/explainers/bias/test_bias_regression.py

@@ -5,6 +5,7 @@
 # For full license text, see the LICENSE file in the repo root or https://opensource.org/licenses/BSD-3-Clause
 #
 import unittest
+import numpy as np
 from omnixai.utils.misc import set_random_seed
 from omnixai.explainers.tabular.agnostic.bias import BiasAnalyzer
 from omnixai.tests.explainers.tasks import TabularRegression
@@ -15,7 +16,7 @@ class TestRegressionBias(unittest.TestCase):
     def test_classification_metric(self):
         set_random_seed()
         task = TabularRegression().train_boston()
-        predict_function = lambda z: task.model.predict_proba(task.transform.transform(z))
+        predict_function = lambda z: task.model.predict(task.transform.transform(z))
 
         explainer = BiasAnalyzer(
             mode="regression",
@@ -24,8 +25,8 @@ def test_classification_metric(self):
             training_targets=task.test_targets
         )
         explainer.explain(
-            feature_column="Sex",
-            feature_value_or_groups="Female"
+            feature_column="LSTAT",
+            feature_value_or_threshold=10
         )