Update app.py

app.py

@@ -6,6 +6,7 @@ from catboost import CatBoostClassifier
 
 clf = CatBoostClassifier()
 clf.load_model("./loan-model.bin")
+
 def predict(customerid: 0,
  gender: 'Female',
  married: 'No',
@@ -19,9 +20,11 @@ def predict(customerid: 0,
  credit_history: 0,
  property_area: 'Rural' 
 )
+
 prediction_array = np.array([customerid, gender, married, dependents, education, self_employed, applicantincome, coapplicantincome, loanamount, loan_amount_term, credit_history, property_area])
 verdict = clf.predict(prediction_array)
 if verdict >= 0.5:
+    
     print('Good Standing - Approved: "Applicant stand a higher chance paying back loan"')
 else:
     print('Bad Standing - Rejected: "Applicant stand a higher chance defaulting payment"')