Github user BryanCutler commented on a diff in the pull request:
https://github.com/apache/spark/pull/10601#discussion_r53820120
--- Diff: python/pyspark/mllib/tree.py ---
@@ -483,28 +519,35 @@ def trainClassifier(cls, data,
categoricalFeaturesInfo,
Method to train a gradient-boosted trees model for
classification.
- :param data: Training dataset: RDD of LabeledPoint.
- Labels should take values {0, 1}.
- :param categoricalFeaturesInfo: Map storing arity of categorical
- features. E.g., an entry (n -> k) indicates that feature
- n is categorical with k categories indexed from 0:
- {0, 1, ..., k-1}.
- :param loss: Loss function used for minimization during gradient
- boosting. Supported: {"logLoss" (default),
- "leastSquaresError", "leastAbsoluteError"}.
- :param numIterations: Number of iterations of boosting.
- (default: 100)
- :param learningRate: Learning rate for shrinking the
- contribution of each estimator. The learning rate
- should be between in the interval (0, 1].
- (default: 0.1)
- :param maxDepth: Maximum depth of the tree. E.g., depth 0 means
- 1 leaf node; depth 1 means 1 internal node + 2 leaf
- nodes. (default: 3)
- :param maxBins: maximum number of bins used for splitting
- features (default: 32) DecisionTree requires maxBins >=
max categories
- :return: GradientBoostedTreesModel that can be used for
- prediction
+ :param data:
+ Training dataset: RDD of LabeledPoint. Labels should take values
+ {0, 1}.
+ :param categoricalFeaturesInfo:
+ Map storing arity of categorical features. E.g., an entry (n ->
+ k) indicates that feature n is categorical with k categories
+ indexed from 0: {0, 1, ..., k-1}.
+ :param loss:
+ Loss function used for minimization during gradient boosting.
+ Supported values: {"logLoss", "leastSquaresError",
--- End diff --
I agree that we should have a consistent format for `Supported Values` or
`Allowed Values` from `classification.py` and `regression.py`. The difference
with the others is that they have a small description for each value too.
@vijaykiran , it would be great to finish this up and get it merged. If
you are unable to, I could take it from here, thanks!
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