code: def test_binary_classification_predict_on_Predictor_instance():
      np.random.seed(0)
  
      (
          df_titanic_train,
          df_titanic_test,
      ) = utils.get_titanic_binary_classification_dataset()
      ml_predictor = utils.train_basic_binary_classifier(
          df_titanic_train
      )
  
      predictions = ml_predictor.predict(df_titanic_test)
      test_score = accuracy_score(predictions, df_titanic_test.survived)
      # Make sure our score is good, but not unreasonably good
      print(test_score)
      assert 0.77 < test_score < 0.805
  
imports: import datetime
  import os
  import random
  import sys
  from auto_ml import Predictor
  from auto_ml.utils_models import load_ml_model
  import dill
  import numpy
  from nose.tools import assert_equal, assert_not_equal, with_setup
  from sklearn.metrics import accuracy_score
  from sklearn.model_selection import train_test_split
  import utils_testing
label_desc: Use image node_id 6 for calling a global function with example usage: test_binary_classification_predict_on_Predictor_instance() without return types