``check_constant_response``
---------------------------

- Available in: GBM, DRF
- Hyperparameter: no

Description
~~~~~~~~~~~

This option checks if a response column is a constant value. If this option is enabled (default), then an exception is thrown if the response column is a constant value. If this option is disabled, then the model will train regardless of the response column being a constant value or not.

Related Parameters
~~~~~~~~~~~~~~~~~~

- None

Example
~~~~~~~

.. example-code::
   .. code-block:: r

	library(h2o)
	h2o.init()

	# import the iris dataset: 
	train.hex <- h2o.importFile("https://s3.amazonaws.com/h2o-public-test-data/smalldata/iris/iris_train.csv")
	train.hex$constantCol <- 1

	# Build a GBM model. This should run successfully when 
	# check_constant_response is set to false.
	iris.gbm.initial <- h2o.gbm(y = 6, x = 1:5, training_frame = train.hex)


   .. code-block:: python

	import h2o
	from h2o.estimators.gbm import H2OGradientBoostingEstimator
	h2o.init()

	# import the iris dataset: 
	train = h2o.import_file("https://s3.amazonaws.com/h2o-public-test-data/smalldata/iris/iris_train.csv")
	train["constantCol"] = 1

	# Build a GBM model. This should run successfully when 
	# check_constant_response is set to false.
	my_gbm = H2OGradientBoostingEstimator(check_constant_response=False)
	my_gbm.train(x=list(range(1,5)), y="constantCol", training_frame=train)