Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/1798#discussion_r15853962
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/tree/DecisionTree.scala ---
@@ -300,6 +293,198 @@ object DecisionTree extends Serializable with Logging
{
new DecisionTree(strategy).train(input)
}
+ /**
+ * Method to train a decision tree model.
+ * The method supports binary and multiclass classification and
regression.
+ * This version takes basic types, for consistency with Python API.
+ *
+ * @param input Training dataset: RDD of
[[org.apache.spark.mllib.regression.LabeledPoint]].
+ * For classification, labels should take values {0, 1,
..., numClasses-1}.
+ * For regression, labels are real numbers.
+ * @param algo "classification" or "regression"
+ * @param numClassesForClassification number of classes for
classification. Default value of 2.
+ * @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 impurity criterion used for information gain calculation
+ * @param maxDepth Maximum depth of the tree.
+ * E.g., depth 0 means 1 leaf node; depth 1 means 1
internal node + 2 leaf nodes.
+ * @param maxBins maximum number of bins used for splitting features
+ * (default Python value = 100)
--- End diff --
It is a little weird to reference the default value in Python here. We can
change it into `suggested value: 100`.
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