Class JointRegressorTrainingNode

java.lang.Object

org.tribuo.common.tree.AbstractTrainingNode<Regressor>

org.tribuo.regression.rtree.impl.JointRegressorTrainingNode

All Implemented Interfaces:

Serializable, Node<Regressor>

public class JointRegressorTrainingNode
extends AbstractTrainingNode<Regressor>

A decision tree node used at training time. Contains a list of the example indices currently found in this node, the current impurity and a bunch of other statistics.

See Also:

• Serialized Form

Field Summary

Fields inherited from class org.tribuo.common.tree.AbstractTrainingNode

DEFAULT_SIZE, depth, greaterThan, lessThanOrEqual, numExamples, split, splitID, splitValue

Constructor Summary

Constructors

Constructor	Description
JointRegressorTrainingNode(RegressorImpurity impurity, Dataset<Regressor> examples, boolean normalize)	Constructor which creates the inverted file.

Method Summary

Modifier and Type	Method	Description
List<AbstractTrainingNode<Regressor>>	buildTree(int[] featureIDs)	Builds a tree according to CART (as it does not do multi-way splits on categorical values like C4.5).
Node<Regressor>	convertTree()	Generates a test time tree (made of SplitNode and LeafNode) from the tree rooted at this node.
double	getImpurity()	The impurity score of this node.

Methods inherited from class org.tribuo.common.tree.AbstractTrainingNode

copy, getDepth, getNextNode, getNumExamples, isLeaf

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Details

JointRegressorTrainingNode

public JointRegressorTrainingNode(RegressorImpurity impurity,
 Dataset<Regressor> examples,
 boolean normalize)

Constructor which creates the inverted file.

Parameters:

impurity - The impurity function to use.

examples - The training data.

normalize - Normalizes the leaves so each leaf has a distribution which sums to 1.0.

Method Details

getImpurity

public double getImpurity()

Description copied from interface: Node

The impurity score of this node.

Returns:

The node impurity.

buildTree

public List<AbstractTrainingNode<Regressor>> buildTree(int[] featureIDs)

Builds a tree according to CART (as it does not do multi-way splits on categorical values like C4.5).

Specified by:

buildTree in class AbstractTrainingNode<Regressor>

Parameters:

featureIDs - Indices of the features available in this split.

Returns:

A possibly empty list of TrainingNodes.

convertTree

public Node<Regressor> convertTree()

Generates a test time tree (made of SplitNode and LeafNode) from the tree rooted at this node.

Specified by:

convertTree in class AbstractTrainingNode<Regressor>

Returns:

A subtree using the SplitNode and LeafNode classes.