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_r312530798
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File path:
mllib/src/main/scala/org/apache/spark/ml/classification/DecisionTreeClassifier.scala
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@@ -210,6 +214,25 @@ class DecisionTreeClassificationModel private[ml] (
rootNode.predictImpl(features).prediction
}
+ /** @group setParam */
+ @Since("3.0.0")
+ def setLeafCol(value: String): this.type = set(leafCol, value)
+
+ @Since("3.0.0")
+ def predictLeaf(features: Vector): Double = predictLeafImpl(features)
Review comment:
Can this go in a superclass? Is there any need to separate predictLeaf from
predictLeafImpl?
Likewise can setLeafCol go in a superclass to avoid repeating it?
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