@keyword_only
@since('1.4.0')
def setParams(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        setParams(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        Sets params for the DecisionTreeRegressor.\n        '
    kwargs = self._input_kwargs
    return self._set(**kwargs)
setParams(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)
Sets params for the DecisionTreeRegressor.
@keyword_only
@since('1.4.0')
def setParams(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        setParams(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        Sets params for the DecisionTreeRegressor.\n        '
    kwargs = self._input_kwargs
    return self._set(**kwargs)