srowen commented on a change in pull request #25383: [SPARK-13677][ML]
Implement Tree-Based Feature Transformation for ML
URL: https://github.com/apache/spark/pull/25383#discussion_r315709454
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File path: mllib/src/main/scala/org/apache/spark/ml/tree/treeModels.scala
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@@ -78,13 +76,34 @@ private[spark] trait DecisionTreeModel {
/** Convert to spark.mllib DecisionTreeModel (losing some information) */
private[spark] def toOld: OldDecisionTreeModel
+
+ /**
+ * @return an iterator that traverses (DFS, left to right) the leaves
+ * in the subtree of this node.
+ */
+ private def leafIterator(node: Node): Iterator[LeafNode] = {
+ node match {
+ case l: LeafNode => Iterator.single(l)
+ case n: InternalNode =>
+ leafIterator(n.leftChild) ++ leafIterator(n.rightChild)
+ }
+ }
+
+ @transient private lazy val leafIndices: Map[LeafNode, Int] = {
+ leafIterator(rootNode).zipWithIndex.toMap
+ }
+
+ /**
+ * @return the index of leaf given a input vector.
+ * The leave are indexed from zero by pre-order.
Review comment:
Nit: leave -> leaves. I might just write: `@return the index of the leaf
corresponding to the feature vector. Leaves are indexed in pre-order from 0.`
(Same for other occurrences)
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