update

app.py

@@ -27,7 +27,7 @@ def churn_prediction(CreditScore,Gender,Age,Tenure,Balance,NumOfProducts,HasCrCa
     pred=saved_model.predict(df)
     pred = pred[0][0]
     churn_prob=str(round(pred,2))
-    churn_prob_d = round(pred,2) * 100
+    churn_prob_d = round(round(pred,2) * 100)
     non_churn_prob_d = 100 - churn_prob_d 
     non_churn_prob = str(round(1-pred,2))
     return {f"probability customer will exit(%) {churn_prob_d}":churn_prob , f"probability customer will stay(%) { non_churn_prob_d}": non_churn_prob}