Update app.py

app.py

@@ -326,7 +326,7 @@ def predict_single(
     # --- Compute derived feature LTV ---
     la = safe_float(loan_amount)
     pv = safe_float(property_value)
-    ltv = np.nan if (pv is None or pv == 0 or np.isnan(pv)) else la / pv
+    ltv = np.nan if (pv is None or pv == 0 or np.isnan(pv)) else (la / pv)*100
 
     input_dict = {
         "loan_limit": [loan_limit],
@@ -348,7 +348,7 @@ def predict_single(
         "construction_type": [construction_type],
         "occupancy_type": [occupancy_type],
         "Secured_by": [Secured_by],
-        "total_units": [safe_float(total_units)],
+        "total_units": [total_units],
         "income": [safe_float(income)],
         "credit_type": [credit_type],
         "Credit_Score": [safe_float(Credit_Score)],