def METHOD_NAME(output_dir):
  """Creates experiment for DNNBoostedTreeCombinedRegressor."""
  (x_train, y_train), (x_test,
                       y_test) = tf.keras.datasets.boston_housing.load_data()
  train_input_fn = tf.compat.v1.estimator.inputs.numpy_input_fn(
      x={"x": x_train},
      y=y_train,
      batch_size=FLAGS.batch_size,
      num_epochs=None,
      shuffle=True)
  eval_input_fn = tf.compat.v1.estimator.inputs.numpy_input_fn(
      x={"x": x_test}, y=y_test, num_epochs=1, shuffle=False)
  feature_columns = [
      feature_column.real_valued_column("x", dimension=_BOSTON_NUM_FEATURES)
  ]
  feature_spec = tf.contrib.layers.create_feature_spec_for_parsing(
      feature_columns)
  serving_input_fn = input_fn_utils.build_parsing_serving_input_fn(feature_spec)
  export_strategies = [
      saved_model_export_utils.make_export_strategy(serving_input_fn)]
  return tf.contrib.learn.Experiment(
      estimator=_get_estimator(output_dir, feature_columns),
      train_input_fn=train_input_fn,
      eval_input_fn=eval_input_fn,
      train_steps=None,
      eval_steps=FLAGS.num_eval_steps,
      eval_metrics=None,
      export_strategies=export_strategies)