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Diffstat (limited to 'python/pyspark/ml/param/shared.py')
| -rw-r--r-- | python/pyspark/ml/param/shared.py | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/python/pyspark/ml/param/shared.py b/python/pyspark/ml/param/shared.py index bc088e4c29..5951247263 100644 --- a/python/pyspark/ml/param/shared.py +++ b/python/pyspark/ml/param/shared.py @@ -444,7 +444,7 @@ class DecisionTreeParams(Params): minInfoGain = Param(Params._dummy(), "minInfoGain", "Minimum information gain for a split to be considered at a tree node.") maxMemoryInMB = Param(Params._dummy(), "maxMemoryInMB", "Maximum memory in MB allocated to histogram aggregation.") cacheNodeIds = Param(Params._dummy(), "cacheNodeIds", "If false, the algorithm will pass trees to executors to match instances with nodes. If true, the algorithm will cache node IDs for each instance. Caching can speed up training of deeper trees.") - + def __init__(self): super(DecisionTreeParams, self).__init__() @@ -460,7 +460,7 @@ class DecisionTreeParams(Params): self.maxMemoryInMB = Param(self, "maxMemoryInMB", "Maximum memory in MB allocated to histogram aggregation.") #: param for If false, the algorithm will pass trees to executors to match instances with nodes. If true, the algorithm will cache node IDs for each instance. Caching can speed up training of deeper trees. self.cacheNodeIds = Param(self, "cacheNodeIds", "If false, the algorithm will pass trees to executors to match instances with nodes. If true, the algorithm will cache node IDs for each instance. Caching can speed up training of deeper trees.") - + def setMaxDepth(self, value): """ Sets the value of :py:attr:`maxDepth`. |