Update app.py

app.py

@@ -351,11 +351,11 @@ def process_dataframe(df):
                        ]:
                 
                 try:
-                    def safe_inverse_transform(le: LabelEncoder, codes: np.ndarray):
-                        known = set(le.classes_)
-                        return np.array([le.inverse_transform([c])[0] if c in known else "Unknown" for c in codes])
-                    df_pred_main[col] = safe_inverse_transform(loaded_label_encoder[col], df_pred_0[col])    
-                    #df_pred_main[col] = loaded_label_encoder[col].inverse_transform(df_pred_main[col].astype(int))
+                    #def safe_inverse_transform(le: LabelEncoder, codes: np.ndarray):
+                    #    known = set(le.classes_)
+                    #    return np.array([le.inverse_transform([c])[0] if c in known else "Unknown" for c in codes])
+                    #df_pred_main[col] = safe_inverse_transform(loaded_label_encoder[col], df_pred_0[col])    
+                    df_pred_main[col] = loaded_label_encoder[col].inverse_transform(df_pred_main[col].astype(int))
                 except ValueError as e:
                     print(f'inverse transform fails value in column {col}: {e}', 'error')