Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/1740#discussion_r15732025
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/tree/configuration/Strategy.scala
---
@@ -60,4 +62,31 @@ class Strategy (
val isMulticlassWithCategoricalFeatures
= isMulticlassClassification && (categoricalFeaturesInfo.size > 0)
+ /**
+ * Java-friendly constructor.
+ *
+ * @param algo classification or regression
+ * @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 numClassesForClassification number of classes for
classification. Default value is 2
+ * leads to binary classification
+ * @param maxBins maximum number of bins used for splitting features
+ * @param categoricalFeaturesInfo A map storing information about the
categorical variables and
+ * the number of discrete values they
take. For example, an entry
+ * (n -> k) implies the feature n is
categorical with k categories
+ * 0, 1, 2, ... , k-1. It's important to
note that features are
+ * zero-indexed.
+ */
+ def this(
+ algo: Algo,
+ impurity: Impurity,
+ maxDepth: Int,
+ numClassesForClassification: Int,
+ maxBins: Int,
+ categoricalFeaturesInfo: java.util.Map[java.lang.Integer,
java.lang.Integer]) {
+ this(algo, impurity, maxDepth, numClassesForClassification, maxBins,
Sort,
+ categoricalFeaturesInfo.map{ case (a, b) => (a.toInt, b.toInt)
}.toMap)
--- End diff --
Could you try `categoricalFeatureInfo.asScala`?
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