code: def test_binary_classification():
      np.random.seed(0)
  
      (
          df_titanic_train,
          df_titanic_test,
      ) = utils.get_titanic_binary_classification_dataset()
  
      column_descriptions = {
          "survived": "output",
          "sex": "categorical",
          "embarked": "categorical",
          "pclass": "categorical",
      }
  
      ml_predictor = Predictor(
          type_of_estimator="classifier",
          column_descriptions=column_descriptions,
      )
  
      ml_predictor.train(
          df_titanic_train, scoring=always_return_ten_thousand
      )
  
      test_score = ml_predictor.score(
          df_titanic_test, df_titanic_test.survived
      )
  
      print("test_score")
      print(test_score)
  
      assert test_score == -10000
  
imports: import os
  import sys
  from auto_ml import Predictor
  import numpy
  import utils_testing
label_desc: Use image node_id 2 for calling a global function with example usage: test_binary_classification() without return types