@since('2.0.0')
def evaluate(self, dataset):
    '\n        Evaluates the model on a test dataset.\n\n        :param dataset:\n          Test dataset to evaluate model on, where dataset is an\n          instance of :py:class:`pyspark.sql.DataFrame`\n        '
    if (not isinstance(dataset, DataFrame)):
        raise ValueError(('dataset must be a DataFrame but got %s.' % type(dataset)))
    java_lr_summary = self._call_java('evaluate', dataset)
    return LinearRegressionSummary(java_lr_summary)
Evaluates the model on a test dataset.

:param dataset:
  Test dataset to evaluate model on, where dataset is an
  instance of :py:class:`pyspark.sql.DataFrame`
@since('2.0.0')
def evaluate(self, dataset):
    '\n        Evaluates the model on a test dataset.\n\n        :param dataset:\n          Test dataset to evaluate model on, where dataset is an\n          instance of :py:class:`pyspark.sql.DataFrame`\n        '
    if (not isinstance(dataset, DataFrame)):
        raise ValueError(('dataset must be a DataFrame but got %s.' % type(dataset)))
    java_lr_summary = self._call_java('evaluate', dataset)
    return LinearRegressionSummary(java_lr_summary)