Score card add fairness for classification notebook

Azure · Nov 2, 2022 · 3364848 · 3364848
1 parent 345364c
commit 3364848
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Showing 2 changed files with 24 additions and 19 deletions.
diff --git a/examples/notebooks/responsibleaidashboard-housing-classification-model-debugging.ipynb b/examples/notebooks/responsibleaidashboard-housing-classification-model-debugging.ipynb
@@ -134,7 +134,7 @@
     "    return X, y\n",
     "\n",
     "target_feature = 'Sold_HigherThan_Median'\n",
-    "categorical_features = []\n",
+    "categorical_features = [\"OverallQual\", \"OverallCond\"]\n",
     "\n",
     "all_data = pd.read_csv(data_path)\n",
     "all_data = all_data.drop(['SalePrice','SalePriceK'], axis=1)\n",
@@ -660,6 +660,11 @@
     "            \"threshold\": \">=0.7\"\n",
     "        },\n",
     "        \"precision_score\": {}\n",
+    "    },\n",
+    "    \"Fairness\": {\n",
+    "        \"metric\": [\"accuracy_score\"],\n",
+    "        \"sensitive_features\": [\"OverallQual\", \"OverallCond\"],\n",
+    "        \"fairness_evaluation_kind\": \"ratio\"\n",
     "    }\n",
     "}\n",
     "\n",
@@ -730,19 +735,19 @@
     "        explain_job.set_limits(timeout=120)\n",
     "        \n",
     "        # Add causal analysis\n",
-    "        causal_job = rai_causal_component(\n",
-    "            rai_insights_dashboard=create_rai_job.outputs.rai_insights_dashboard,\n",
-    "            treatment_features=treatment_features,\n",
-    "        )\n",
-    "        causal_job.set_limits(timeout=120)\n",
+    "        # causal_job = rai_causal_component(\n",
+    "        #     rai_insights_dashboard=create_rai_job.outputs.rai_insights_dashboard,\n",
+    "        #     treatment_features=treatment_features,\n",
+    "        # )\n",
+    "        # causal_job.set_limits(timeout=120)\n",
     "        \n",
     "        # Add counterfactual analysis\n",
-    "        counterfactual_job = rai_counterfactual_component(\n",
-    "            rai_insights_dashboard=create_rai_job.outputs.rai_insights_dashboard,\n",
-    "            total_cfs=10,\n",
-    "            desired_class='opposite',\n",
-    "        )\n",
-    "        counterfactual_job.set_limits(timeout=600)\n",
+    "        # counterfactual_job = rai_counterfactual_component(\n",
+    "        #     rai_insights_dashboard=create_rai_job.outputs.rai_insights_dashboard,\n",
+    "        #     total_cfs=10,\n",
+    "        #     desired_class='opposite',\n",
+    "        # )\n",
+    "        # counterfactual_job.set_limits(timeout=600)\n",
     "        \n",
     "        # Add error analysis\n",
     "        erroranalysis_job = rai_erroranalysis_component(\n",
@@ -754,8 +759,8 @@
     "        rai_gather_job = rai_gather_component(\n",
     "            constructor=create_rai_job.outputs.rai_insights_dashboard,\n",
     "            insight_1=explain_job.outputs.explanation,\n",
-    "            insight_2=causal_job.outputs.causal,\n",
-    "            insight_3=counterfactual_job.outputs.counterfactual,\n",
+    "            # insight_2=causal_job.outputs.causal,\n",
+    "            # insight_3=counterfactual_job.outputs.counterfactual,\n",
     "            insight_4=erroranalysis_job.outputs.error_analysis,\n",
     "        )\n",
     "        rai_gather_job.set_limits(timeout=120)\n",

diff --git a/src/responsibleai/rai_analyse/_score_card/classification_components.py b/src/responsibleai/rai_analyse/_score_card/classification_components.py
@@ -357,11 +357,11 @@ def get_fairness_bar_plot(data):
         ]
         x_data = [
             100 * (get_metric(
-                "selection_rate",
-                data[c]["y_test"],
-                data[c]["y_pred"]),
-                data[c]["pos_label"]
-            )
+                metric="selection_rate",
+                y_test=data[c]["y_test"],
+                y_pred=data[c]["y_pred"],
+                pos_label=data[c]["pos_label"]
+            ))
             for c in data
         ]
         x_data = [[x, 100 - x] for x in x_data]