@since('2.4.0')
def evaluateEachIteration(self, dataset, loss):
    '\n        Method to compute error or loss for every iteration of gradient boosting.\n\n        :param dataset:\n            Test dataset to evaluate model on, where dataset is an\n            instance of :py:class:`pyspark.sql.DataFrame`\n        :param loss:\n            The loss function used to compute error.\n            Supported options: squared, absolute\n        '
    return self._call_java('evaluateEachIteration', dataset, loss)
Method to compute error or loss for every iteration of gradient boosting.

:param dataset:
    Test dataset to evaluate model on, where dataset is an
    instance of :py:class:`pyspark.sql.DataFrame`
:param loss:
    The loss function used to compute error.
    Supported options: squared, absolute
@since('2.4.0')
def evaluateEachIteration(self, dataset, loss):
    '\n        Method to compute error or loss for every iteration of gradient boosting.\n\n        :param dataset:\n            Test dataset to evaluate model on, where dataset is an\n            instance of :py:class:`pyspark.sql.DataFrame`\n        :param loss:\n            The loss function used to compute error.\n            Supported options: squared, absolute\n        '
    return self._call_java('evaluateEachIteration', dataset, loss)