text: from sklearn.metrics import make_scorer
  
  def equi_loans_val(y_true, y_pred):
      valid_predictions = 0
      invalid_predictions = 0
  
      for i in range(0, len(y_pred)):
          if (y_pred[i] == 1):
              if (y_true.array[i] == 1):
                  valid_predictions += 1
              else:
                  invalid_predictions += 1
  
      return valid_predictions*5-invalid_predictions
  
  
  my_scorer = make_scorer(equi_loans_val, greater_is_better=True)
  