Update app.py

app.py

@@ -423,11 +423,11 @@ def main():
                 st.subheader(":orange[Neural Network]")
                 ann = load_model('ann.h5')
                 pred_proba = ann.predict(data_input)
+                pred = np.where(pred_proba < 0.5, 0, 1)
                 if pred == 1:
                     st.write(":orange[__Le pret peut etre octroyer__] :white_check_mark:")
                 else: 
                     st.write(":red[__Desole,...__] :disappointed:")
-                pred = np.where(pred_proba < 0.5, 0, 1)
                 loan_status = np.array(['N','Y'])
                 prediction = pd.DataFrame(loan_status[pred], columns=['prediction'])
                 df = pd.concat([data_input, prediction], axis=1)