DecisionTreeModel (Spark 3.4.0 JavaDoc)

All Known Implementing Classes:

DecisionTreeClassificationModel, DecisionTreeRegressionModel
```
public interface DecisionTreeModel
```
Abstraction for Decision Tree models.

Method Summary

All Methods Instance Methods Abstract Methods
Modifier and Type	Method and Description
`int`	`depth()` Depth of the tree.
`StructField`	`getLeafField(String leafCol)`
`NominalAttribute`	`leafAttr()`
`scala.collection.Iterator<LeafNode>`	`leafIterator(Node node)`
`int`	`maxSplitFeatureIndex()` Trace down the tree, and return the largest feature index used in any split.
`int`	`numLeave()`
`int`	`numNodes()` Number of nodes in tree, including leaf nodes.
`double`	`predictLeaf(Vector features)`
`Node`	`rootNode()` Root of the decision tree
`String`	`toDebugString()` Full description of model
`DecisionTreeModel`	`toOld()` Convert to spark.mllib DecisionTreeModel (losing some information)
`String`	`toString()` Summary of the model

- Method Detail
  - depth
```
int depth()
```
    Depth of the tree. E.g.: Depth 0 means 1 leaf node. Depth 1 means 1 internal node and 2 leaf nodes.
    
    Returns:
    
    (undocumented)
  - getLeafField
```
StructField getLeafField(String leafCol)
```
  - leafAttr
```
NominalAttribute leafAttr()
```
  - leafIterator
```
scala.collection.Iterator<LeafNode> leafIterator(Node node)
```
    Parameters:
    
    node - (undocumented)
    
    Returns:
    
    an iterator that traverses (DFS, left to right) the leaves in the subtree of this node.
  - maxSplitFeatureIndex
```
int maxSplitFeatureIndex()
```
    Trace down the tree, and return the largest feature index used in any split.
    
    Returns:
    
    Max feature index used in a split, or -1 if there are no splits (single leaf node).
  - numLeave
```
int numLeave()
```
  - numNodes
```
int numNodes()
```
    Number of nodes in tree, including leaf nodes.
  - predictLeaf
```
double predictLeaf(Vector features)
```
    Parameters:
    
    features - (undocumented)
    
    Returns:
    
    The index of the leaf corresponding to the feature vector. Leaves are indexed in pre-order from 0.
  - rootNode
```
Node rootNode()
```
    Root of the decision tree
  - toDebugString
```
String toDebugString()
```
    Full description of model
  - toOld
```
DecisionTreeModel toOld()
```
    Convert to spark.mllib DecisionTreeModel (losing some information)
  - toString
```
String toString()
```
    Summary of the model
    
    Overrides:
    
    toString in class Object

Interface DecisionTreeModel

Method Summary

Method Detail

depth

getLeafField

leafAttr

leafIterator

maxSplitFeatureIndex

numLeave

numNodes

predictLeaf

rootNode

toDebugString

toOld

toString