Scikit learn 什么是'；tree.value'；Spark ML中sklearn的决策树？

比较Scikit learn和Spark ML的

决策树

模型。以下两个模型非常匹配。我无法映射的是

值

Spark ML

DecisionTree

数据的架构：

root
 |-- id: integer (nullable = true)
 |-- prediction: double (nullable = true)
 |-- impurity: double (nullable = true)
 |-- impurityStats: array (nullable = true)
 |    |-- element: double (containsNull = true)
 |-- gain: double (nullable = true)
 |-- leftChild: integer (nullable = true)
 |-- rightChild: integer (nullable = true)
 |-- split: struct (nullable = true)
 |    |-- featureIndex: integer (nullable = true)
 |    |-- leftCategoriesOrThreshold: array (nullable = true)
 |    |    |-- element: double (containsNull = true)
 |    |-- numCategories: integer (nullable = true)

sklearn tree.feature        --> sparkML root.split.featureIndex
sklearn tree.threshold      --> sparkML.root.leftCategoriesOrThreshold
sklearn tree.children_left  --> sparkML root.leftChild
sklearn tree.children_right --> sparkML root.rightChild
sklearn tree.value          --> sparkML root.?

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可能是树的预言吗？