def METHOD_NAME(csv_file_name):
  # Cycle between 5 latent values over a period of 100. This leads to a very
  # smooth periodic component (and a small model), which is a good fit for our
  # example data. Modeling high-frequency periodic variations will require a
  # higher cycle_num_latent_values.
  structural = tf.contrib.timeseries.StructuralEnsembleRegressor(
      periodicities=100, num_features=1, cycle_num_latent_values=5)
  return train_and_predict(structural, csv_file_name, training_steps=150)