Update app.py

app.py

@@ -1,3 +1,5 @@
+# with cluster profiles 
+
 import gradio as gr
 import pickle
 import pandas as pd
@@ -12,12 +14,11 @@ with open(filename, 'rb') as f:
 # Setup SHAP
 explainer = shap.Explainer(loaded_model)
 
-# Employee Profiles (Adjusted Top Performer)
+# Employee Profiles (From SPSS 3-Cluster Solution)
 employee_profiles = {
-    "📈 High Potential Employee": [4, 5, 5, 3, 4, 5],
-    "🏆 Top Performer": [5, 5, 5, 3, 5, 5],  # Reduced workload
-    "⚠️ At-Risk Employee": [2, 2, 2, 4, 2, 2],
-    "🔥 Burnt-Out Employee": [1, 2, 2, 5, 1, 1]
+    "🏆 Leslie Knope": [4.716, 4.792, 4.864, 4.588, 4.849, 4.601],  # Cluster group 1 averages - high engagement, strong support, high workload
+    "⚠️ Kevin Malone": [3.045, 3.122, 3.129, 2.886, 3.113, 2.197],  # Cluster group 2 averages - disengaged, low recognition, weak support
+    "🌱 Jim Halpert": [3.885, 3.992, 4.119, 3.704, 4.090, 3.377] # Cluster group 3 averages - Moderately engaged, could be more recognized - room to grow
 }
 
 # Define the prediction function