Update app.py

app.py

@@ -36,4 +36,22 @@ if st.button("Predict disease progression score"):
     # Directly predict: model was trained on X without extra scaler
     score = lr.predict(x)[0]
 
-    st.success(f"Estimated disease progression score after 1 year: **{score:.2f}**")
+    # --- Convert score -> risk label (simple, educational thresholds) ---
+    # Typical target range in load_diabetes is about 25–350
+    if score < 120:
+        risk = "Low progression risk"
+        simple_label = "Likely NOT diabetic / low concern (for this dataset)"
+    elif score < 200:
+        risk = "Medium progression risk"
+        simple_label = "Borderline / moderate concern"
+    else:
+        risk = "High progression risk"
+        simple_label = "High concern / likely diabetic (for this dataset)"
+
+    st.success(f"Estimated disease progression score after 1 year: **{score:.2f}**")
+    st.info(f"Risk level: **{risk}**\n\nInterpretation: {simple_label}")
+
+    st.caption(
+        "⚠️ These thresholds are **for learning only** based on the sklearn dataset. "
+        "This does **not** replace real medical diagnosis."
+    )