Class AbstractTrainingNode<T extends Output<T>>

java.lang.Object

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

All Implemented Interfaces:

Serializable, Node<T>

Direct Known Subclasses:

ClassifierTrainingNode, JointRegressorTrainingNode, RegressorTrainingNode

public abstract class AbstractTrainingNode<T extends Output<T>>
extends Object
implements Node<T>

Base class for decision tree nodes used at training time.

See Also:

• Serialized Form

Field Summary

Fields

Modifier and Type	Field	Description
protected static final int	DEFAULT_SIZE	Default buffer size used in the split operation.
protected final int	depth
protected AbstractTrainingNode<T>	greaterThan
protected AbstractTrainingNode<T>	lessThanOrEqual
protected final int	numExamples
protected boolean	split
protected int	splitID
protected double	splitValue

Constructor Summary

Constructors

Modifier	Constructor	Description
protected	AbstractTrainingNode(int depth, int numExamples)	Builds an abstract training node.

Method Summary

Modifier and Type	Method	Description
abstract List<AbstractTrainingNode<T>>	buildTree(int[] indices)
abstract Node<T>	convertTree()	Converts a tree from a training representation to the final inference time representation.
Node<T>	copy()	Copies the node and it's children.
int	getDepth()	The depth of this node in the tree.
Node<T>	getNextNode(SparseVector example)	Returns the next node in the tree based on the supplied example, or null if it's a leaf.
int	getNumExamples()	The number of training examples in this node.
boolean	isLeaf()	Is it a leaf node?

Methods inherited from class java.lang.Object

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

Methods inherited from interface org.tribuo.common.tree.Node

getImpurity

Field Details

DEFAULT_SIZE

protected static final int DEFAULT_SIZE

Default buffer size used in the split operation.

See Also:

• Constant Field Values

depth

protected final int depth

numExamples

protected final int numExamples

split

protected boolean split

splitID

protected int splitID

splitValue

protected double splitValue

greaterThan

protected AbstractTrainingNode<T extends Output<T>> greaterThan

lessThanOrEqual

protected AbstractTrainingNode<T extends Output<T>> lessThanOrEqual

Constructor Details

AbstractTrainingNode

protected AbstractTrainingNode(int depth,
 int numExamples)

Builds an abstract training node.

Parameters:

depth - The depth of this node.

numExamples - The number of examples in this node.

Method Details

buildTree

public abstract List<AbstractTrainingNode<T>> buildTree(int[] indices)

convertTree

public abstract Node<T> convertTree()

Converts a tree from a training representation to the final inference time representation.

Returns:

The converted subtree.

getDepth

public int getDepth()

The depth of this node in the tree.

Returns:

The depth.

getNextNode

public Node<T> getNextNode(SparseVector example)

Description copied from interface: Node

Returns the next node in the tree based on the supplied example, or null if it's a leaf.

Specified by:

getNextNode in interface Node<T extends Output<T>>

Parameters:

example - The example.

Returns:

The next node down in the tree.

getNumExamples

public int getNumExamples()

The number of training examples in this node.

Returns:

The number of training examples in this node.

isLeaf

public boolean isLeaf()

Description copied from interface: Node

Is it a leaf node?

Specified by:

isLeaf in interface Node<T extends Output<T>>

Returns:

True if it's a leaf node.

copy

public Node<T> copy()

Description copied from interface: Node

Copies the node and it's children.

Specified by:

copy in interface Node<T extends Output<T>>

Returns:

A deep copy.