weka.classifiers.trees.ft

Class FTtree

java.lang.Object

weka.classifiers.Classifier

weka.classifiers.trees.lmt.LogisticBase

weka.classifiers.trees.ft.FTtree

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable, CapabilitiesHandler, OptionHandler, RevisionHandler, WeightedInstancesHandler

Direct Known Subclasses:

FTInnerNode, FTLeavesNode, FTNode

public abstract class FTtree
extends LogisticBase

Abstract class for Functional tree structure.

Version:

$Revision: 1.4 $

Author:

Jo\~{a}o Gama, Carlos Ferreira

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
FTtree()

Method Summary

Modifier and Type	Method and Description
int	assignIDs(int lastID) Assigns unique IDs to all nodes in the tree
int	assignLeafModelNumbers(int leafCounter) Assigns numbers to the logistic regression models at the leaves of the tree
abstract void	buildClassifier(Instances data) Method for building a Functional Tree (only called for the root node).
abstract void	buildTree(Instances data, SimpleLinearRegression[][] higherRegressions, double totalInstanceWeight, double higherNumParameters) Abstract method for building the tree structure.
void	cleanup() Cleanup in order to save memory.
abstract double[]	distributionForInstance(Instance instance) Returns the class probabilities for an instance given by the Functional tree.
int	getConstError(double[] probsConst)
java.lang.String	getModelParameters() Returns a string describing the number of LogitBoost iterations performed at this node, the total number of LogitBoost iterations performed (including iterations at higher levels in the tree), and the number of training examples at this node.
java.util.Vector	getNodes() Return a list of all inner nodes in the tree
void	getNodes(java.util.Vector nodeList) Fills a list with all inner nodes in the tree
int	getNumInnerNodes() Method to count the number of inner nodes in the tree
int	getNumLeaves() Returns the number of leaves in the tree.
java.lang.String	getRevision() Returns the revision string.
java.lang.String	graph() Returns graph describing the tree.
boolean	hasModels() Returns true if the logistic regression model at this node has changed compared to the one at the parent node.
double[]	modelDistributionForInstance(Instance instance) Returns the class probabilities for an instance according to the logistic model at the node.
java.lang.String	modelsToString() Returns a string describing the logistic regression function at the node.
int	numLeaves() Returns the number of leaves (normal count).
int	numNodes() Returns the number of nodes.
abstract double	prune() Abstract Method that prunes a tree using C4.5 pruning procedure.
java.lang.String	toString() Returns a description of the Functional tree (tree structure and logistic models)

Methods inherited from class weka.classifiers.trees.lmt.LogisticBase

getMaxIterations, getNumRegressions, getUseAIC, getUsedAttributes, getWeightTrimBeta, percentAttributesUsed, setHeuristicStop, setMaxIterations, setUseAIC, setWeightTrimBeta

Methods inherited from class weka.classifiers.Classifier

classifyInstance, debugTipText, forName, getCapabilities, getDebug, getOptions, listOptions, makeCopies, makeCopy, setDebug, setOptions

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

FTtree

public FTtree()

Method Detail

buildClassifier

public abstract void buildClassifier(Instances data)
                              throws java.lang.Exception

Method for building a Functional Tree (only called for the root node). Grows an initial Functional Tree.

Overrides:

buildClassifier in class LogisticBase

Parameters:

data - the data to train with

Throws:

java.lang.Exception - if something goes wrong

buildTree

public abstract void buildTree(Instances data,
                               SimpleLinearRegression[][] higherRegressions,
                               double totalInstanceWeight,
                               double higherNumParameters)
                        throws java.lang.Exception

Abstract method for building the tree structure. Builds a logistic model, splits the node and recursively builds tree for child nodes.

Parameters:

data - the training data passed on to this node

higherRegressions - An array of regression functions produced by LogitBoost at higher levels in the tree. They represent a logistic regression model that is refined locally at this node.

totalInstanceWeight - the total number of training examples

higherNumParameters - effective number of parameters in the logistic regression model built in parent nodes

Throws:

java.lang.Exception - if something goes wrong

prune

public abstract double prune()
                      throws java.lang.Exception

Abstract Method that prunes a tree using C4.5 pruning procedure.

Throws:

java.lang.Exception - if something goes wrong

getNumInnerNodes

public int getNumInnerNodes()

Method to count the number of inner nodes in the tree

Returns:

the number of inner nodes

getNumLeaves

public int getNumLeaves()

Returns the number of leaves in the tree. Leaves are only counted if their logistic model has changed compared to the one of the parent node.

Returns:

the number of leaves

getNodes

public java.util.Vector getNodes()

Return a list of all inner nodes in the tree

Returns:

the list of nodes

getNodes

public void getNodes(java.util.Vector nodeList)

Fills a list with all inner nodes in the tree

Parameters:

nodeList - the list to be filled

getConstError

public int getConstError(double[] probsConst)

Type Parameters:

any - probsConst

hasModels

public boolean hasModels()

Returns true if the logistic regression model at this node has changed compared to the one at the parent node.

Returns:

whether it has changed

modelDistributionForInstance

public double[] modelDistributionForInstance(Instance instance)
                                      throws java.lang.Exception

Returns the class probabilities for an instance according to the logistic model at the node.

Parameters:

instance - the instance

Returns:

the array of probabilities

Throws:

java.lang.Exception

distributionForInstance

public abstract double[] distributionForInstance(Instance instance)
                                          throws java.lang.Exception

Returns the class probabilities for an instance given by the Functional tree.

Overrides:

distributionForInstance in class LogisticBase

Parameters:

instance - the instance

Returns:

the array of probabilities

Throws:

java.lang.Exception - if distribution can't be computed successfully

toString

public java.lang.String toString()

Returns a description of the Functional tree (tree structure and logistic models)

Overrides:

toString in class LogisticBase

Returns:

describing string

numLeaves

public int numLeaves()

Returns the number of leaves (normal count).

Returns:

the number of leaves

numNodes

public int numNodes()

Returns the number of nodes.

Returns:

the number of nodes

getModelParameters

public java.lang.String getModelParameters()

Returns a string describing the number of LogitBoost iterations performed at this node, the total number of LogitBoost iterations performed (including iterations at higher levels in the tree), and the number of training examples at this node.

Returns:

the describing string

assignIDs

public int assignIDs(int lastID)

Assigns unique IDs to all nodes in the tree

assignLeafModelNumbers

public int assignLeafModelNumbers(int leafCounter)

Assigns numbers to the logistic regression models at the leaves of the tree

modelsToString

public java.lang.String modelsToString()

Returns a string describing the logistic regression function at the node.

graph

public java.lang.String graph()
                       throws java.lang.Exception

Returns graph describing the tree.

Throws:

java.lang.Exception - if something goes wrong

cleanup

public void cleanup()

Cleanup in order to save memory.

Overrides:

cleanup in class LogisticBase

getRevision

public java.lang.String getRevision()

Returns the revision string.

Specified by:

getRevision in interface RevisionHandler

Overrides:

getRevision in class LogisticBase

Returns:

the revision