Update app.py

app.py

@@ -192,9 +192,9 @@ def predict_inverse(hardness_target, ys_target, request: gr.Request):
         [el['name'] for el in domain],
         [[x] for x in x_best]))
     optimized_x = pd.DataFrame.from_dict(best_params)
-    for c in optimized_x.columns:
-        if c in continuous_variables:
-            optimized_x[c]=optimized_x[c]*(scaling_factors[c][1]-scaling_factors[c][0])+scaling_factors[c][0]
+    #for c in optimized_x.columns:
+     #   if c in continuous_variables:
+      #      optimized_x[c]=optimized_x[c]*(scaling_factors[c][1]-scaling_factors[c][0])+scaling_factors[c][0]
     optimized_x = optimized_x[['PROPERTY: Calculated Density (g/cm$^3$)',
                                'PROPERTY: Calculated Young modulus (GPa)',
                                'Preprocessing method ANNEAL',