Update app.py

app.py

@@ -276,8 +276,8 @@ def predict(
 # Buttons
 # =========================
 def load_at_risk_group():
-    # At-risk group = Cluster 3 (lowest means)
-    target = {v: CLUSTER_3[v] for v in ALL_DRIVER_VARS}
+    # At-risk group = average of the two lowest clusters (2 and 3)
+    target = {v: (CLUSTER_2[v] + CLUSTER_3[v]) / 2.0 for v in ALL_DRIVER_VARS}
 
     headline, drivers_fig, shap_fig = predict(
         target["Engagement"],
@@ -304,28 +304,27 @@ def load_at_risk_group():
 
 
 def apply_recommendation():
-    # Recommendation = move toward high performers
-    # average of Cluster 1 and Cluster 2
-    avg = {v: (CLUSTER_1[v] + CLUSTER_2[v]) / 2.0 for v in ALL_DRIVER_VARS}
+    # Recommendation = highest cluster (Cluster 1)
+    target = {v: CLUSTER_1[v] for v in ALL_DRIVER_VARS}
 
     headline, drivers_fig, shap_fig = predict(
-        avg["Engagement"],
-        avg["SupportiveGM"],
-        avg["WellBeing"],
-        avg["WorkEnvironment"],
-        avg["Voice"],
-        avg["DecisionAutonomy"],
-        avg["Workload"],
+        target["Engagement"],
+        target["SupportiveGM"],
+        target["WellBeing"],
+        target["WorkEnvironment"],
+        target["Voice"],
+        target["DecisionAutonomy"],
+        target["Workload"],
     )
 
     return (
-        avg["Engagement"],
-        avg["SupportiveGM"],
-        avg["WellBeing"],
-        avg["WorkEnvironment"],
-        avg["Voice"],
-        avg["DecisionAutonomy"],
-        avg["Workload"],
+        target["Engagement"],
+        target["SupportiveGM"],
+        target["WellBeing"],
+        target["WorkEnvironment"],
+        target["Voice"],
+        target["DecisionAutonomy"],
+        target["Workload"],
         headline,
         drivers_fig,
         shap_fig,