相当于 ml.DecisionTreeClassificationModel 中的 mllib.DecisionTreeModel.toDebugString() [英] Equivalent of mllib.DecisionTreeModel.toDebugString() in ml.DecisionTreeClassificationModel

问题描述

正如问题所说，org.apache.spark.ml 中是否有任何相当于 Spark org.apache.spark.mllib.tree.model.DecisionTreeClassificationModel.toDebugString() 的东西.分类.决策树分类模型

As the question says, is there any equivalent of Spark org.apache.spark.mllib.tree.model.DecisionTreeClassificationModel.toDebugString() in org.apache.spark.ml.classification.DecisionTreeClassificationModel

我已经浏览了后者的 API 文档，发现这个方法 rootNode() 返回一个 org.apache.spark.ml.tree.Node 对象这似乎是一个递归对象，那么我应该使用这个类来自己构建树结构吗?

I have gone through the API doc of the latter and found this method rootNode() which gives back a org.apache.spark.ml.tree.Node object which seems to be a recursive object, so should I use this class instead to build the tree structure myself?

期待中的感谢.

推荐答案

org.apache.spark.ml.classification.DecisionTreeClassificationModel 已经实现了 toDebugString() 方法，因为它具有 DecisionTreeModel 作为特征.

org.apache.spark.ml.classification.DecisionTreeClassificationModel already have a toDebugString() method implemented because it has DecisionTreeModel as a trait.

示例:

class org.apache.spark.ml.classification.DecisionTreeClassificationModel
DecisionTreeClassificationModel of depth 1 with 3 nodes
  If (feature 378 <= 71.0)
   Predict: 1.0
  Else (feature 378 > 71.0)
   Predict: 0.0

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