Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/11581#discussion_r56082025
--- Diff: mllib/src/main/scala/org/apache/spark/ml/tree/treeModels.scala ---
@@ -101,3 +109,127 @@ private[ml] trait TreeEnsembleModel {
/** Total number of nodes, summed over all trees in the ensemble. */
lazy val totalNumNodes: Int = trees.map(_.numNodes).sum
}
+
+/** Helper classes for tree model persistence */
+private[ml] object DecisionTreeModelReadWrite {
+
+ /**
+ * Info for a [[org.apache.spark.ml.tree.Split]]
+ *
+ * @param featureIndex Index of feature split on
+ * @param leftCategoriesOrThreshold For categorical feature, set of
leftCategories.
+ * For continuous feature, threshold.
+ * @param numCategories For categorical feature, number of categories.
+ * For continuous feature, -1.
+ */
+ case class SplitData(
+ featureIndex: Int,
+ leftCategoriesOrThreshold: Array[Double],
+ numCategories: Int) {
+
+ def getSplit: Split = {
+ if (numCategories != -1) {
+ new CategoricalSplit(featureIndex, leftCategoriesOrThreshold,
numCategories)
+ } else {
+ assert(leftCategoriesOrThreshold.length == 1, s"DecisionTree split
data expected" +
+ s" 1 threshold for ContinuousSplit, but found thresholds: " +
+ leftCategoriesOrThreshold.mkString(", "))
+ new ContinuousSplit(featureIndex, leftCategoriesOrThreshold(0))
+ }
+ }
+ }
+
+ object SplitData {
+ def apply(split: Split): SplitData = split match {
+ case s: CategoricalSplit =>
+ SplitData(s.featureIndex, s.leftCategories, s.numCategories)
+ case s: ContinuousSplit =>
+ SplitData(s.featureIndex, Array(s.threshold), -1)
+ }
+ }
+
+ /**
+ * Info for a [[Node]]
+ *
+ * @param id Index used for tree reconstruction. Indices follow an
in-order traversal.
+ * @param impurityStats Stats array. Impurity type is stored in
metadata.
+ * @param gain Gain, or arbitrary value if leaf node.
--- End diff --
I like having this weaker public guarantee: people should not assume
anything about the values
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