Github user BryanCutler commented on a diff in the pull request:
https://github.com/apache/spark/pull/10601#discussion_r50582271
--- Diff: python/pyspark/mllib/tree.py ---
@@ -213,20 +224,28 @@ def trainRegressor(cls, data, categoricalFeaturesInfo,
"""
Train a DecisionTreeModel for regression.
- :param data: Training data: RDD of LabeledPoint.
- Labels are real numbers.
- :param categoricalFeaturesInfo: Map from categorical feature
- index to number of categories.
- Any feature not in this map is treated as continuous.
- :param impurity: Supported values: "variance"
- :param maxDepth: Max depth of tree.
- E.g., depth 0 means 1 leaf node.
- Depth 1 means 1 internal node + 2 leaf nodes.
- :param maxBins: Number of bins used for finding splits at each
- node.
- :param minInstancesPerNode: Min number of instances required at
- child nodes to create the parent split
- :param minInfoGain: Min info gain required to create a split
+ :param data:
+ Training data: RDD of LabeledPoint. Labels are real numbers.
+ :param categoricalFeaturesInfo:
+ Map from categorical feature index to number of categories. Any
+ feature not in this map is treated as continuous.
+ :param impurity:
+ Supported values: "variance".
+ (default: "variance")
+ :param maxDepth:
+ Max depth of tree. E.g., depth 0 means 1 leaf node. Depth 1
+ means 1 internal node + 2 leaf nodes.
+ (default: 5)
+ :param maxBins:
+ Number of bins used for finding splits at each node.
+ (default: 32)
+ :param minInstancesPerNode:
+ Min number of instances required at child nodes to create the
+ parent split.
+ (default: 1)
+ :param minInfoGain:
+ Min info gain required to create a split.
+ (default: 0.0)
:return: DecisionTreeModel
--- End diff --
:return: formatting
---
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