@keyword_only
def __init__(self, featuresCol='features', labelCol='label', predictionCol='prediction', maxDepth=5, maxBins=32, minInstancesPerNode=1, minInfoGain=0.0, maxMemoryInMB=256, cacheNodeIds=False, checkpointInterval=10, impurity='variance', seed=None, varianceCol=None, weightCol=None, leafCol='', minWeightFractionPerNode=0.0):
    '\n        __init__(self, featuresCol="features", labelCol="label", predictionCol="prediction",                  maxDepth=5, maxBins=32, minInstancesPerNode=1, minInfoGain=0.0,                  maxMemoryInMB=256, cacheNodeIds=False, checkpointInterval=10,                  impurity="variance", seed=None, varianceCol=None, weightCol=None,                  leafCol="", minWeightFractionPerNode=0.0)\n        '
    super(DecisionTreeRegressor, self).__init__()
    self._java_obj = self._new_java_obj('org.apache.spark.ml.regression.DecisionTreeRegressor', self.uid)
    self._setDefault(maxDepth=5, maxBins=32, minInstancesPerNode=1, minInfoGain=0.0, maxMemoryInMB=256, cacheNodeIds=False, checkpointInterval=10, impurity='variance', leafCol='', minWeightFractionPerNode=0.0)
    kwargs = self._input_kwargs
    self.setParams(**kwargs)
__init__(self, featuresCol="features", labelCol="label", predictionCol="prediction",                  maxDepth=5, maxBins=32, minInstancesPerNode=1, minInfoGain=0.0,                  maxMemoryInMB=256, cacheNodeIds=False, checkpointInterval=10,                  impurity="variance", seed=None, varianceCol=None, weightCol=None,                  leafCol="", minWeightFractionPerNode=0.0)
@keyword_only
def __init__(self, featuresCol='features', labelCol='label', predictionCol='prediction', maxDepth=5, maxBins=32, minInstancesPerNode=1, minInfoGain=0.0, maxMemoryInMB=256, cacheNodeIds=False, checkpointInterval=10, impurity='variance', seed=None, varianceCol=None, weightCol=None, leafCol=, minWeightFractionPerNode=0.0):
    '\n        \n        '
    super(DecisionTreeRegressor, self).__init__()
    self._java_obj = self._new_java_obj('org.apache.spark.ml.regression.DecisionTreeRegressor', self.uid)
    self._setDefault(maxDepth=5, maxBins=32, minInstancesPerNode=1, minInfoGain=0.0, maxMemoryInMB=256, cacheNodeIds=False, checkpointInterval=10, impurity='variance', leafCol=, minWeightFractionPerNode=0.0)
    kwargs = self._input_kwargs
    self.setParams(**kwargs)