weka.classifiers.j48
Class ClassifierTree

java.lang.Object
  |
  +--weka.classifiers.j48.ClassifierTree

All Implemented Interfaces:

Drawable, java.io.Serializable

Direct Known Subclasses:

C45PruneableClassifierTree, PruneableClassifierTree

public class ClassifierTree

extends java.lang.Object

implements Drawable, java.io.Serializable

Class for handling a tree structure used for classification.

Author:

Eibe Frank (eibe@cs.waikato.ac.nz)

See Also:

Serialized Form

Field Summary

protected int	m_id The id for the node.
protected boolean	m_isEmpty True if node is empty.
protected boolean	m_isLeaf True if node is leaf.
protected ClassifierSplitModel	m_localModel Local model at node.
protected ClassifierTree[]	m_sons References to sons.
protected Distribution	m_test The pruning instances.
protected ModelSelection	m_toSelectModel The model selection method.
protected Instances	m_train The training instances.

Constructor Summary

ClassifierTree(ModelSelection toSelectLocModel)
Constructor.

Method Summary

int	assignIDs(int lastID) Assigns a uniqe id to every node in the tree.
void	buildClassifier(Instances data) Method for building a classifier tree.
void	buildTree(Instances data, boolean keepData) Builds the tree structure.
void	buildTree(Instances train, Instances test, boolean keepData) Builds the tree structure with hold out set
double	classifyInstance(Instance instance) Classifies an instance.
void	cleanup(Instances justHeaderInfo) Cleanup in order to save memory.
double[]	distributionForInstance(Instance instance, boolean useLaplace) Returns class probabilities for a weighted instance.
protected ClassifierTree	getNewTree(Instances data) Returns a newly created tree.
protected ClassifierTree	getNewTree(Instances train, Instances test) Returns a newly created tree.
java.lang.String	graph() Returns graph describing the tree.
protected static long	nextID() Gets the next unique node ID.
int	numLeaves() Returns number of leaves in tree structure.
int	numNodes() Returns number of nodes in tree structure.
java.lang.String	prefix() Returns tree in prefix order.
protected static void	resetID() Resets the unique node ID counter (e.g.
java.lang.StringBuffer[]	toSource(java.lang.String className) Returns source code for the tree as an if-then statement.
java.lang.String	toString() Prints tree structure.

Methods inherited from class java.lang.Object

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

Field Detail

m_toSelectModel

protected ModelSelection m_toSelectModel

The model selection method.

m_localModel

protected ClassifierSplitModel m_localModel

Local model at node.

m_sons

protected ClassifierTree[] m_sons

References to sons.

m_isLeaf

protected boolean m_isLeaf

True if node is leaf.

m_isEmpty

protected boolean m_isEmpty

True if node is empty.

m_train

protected Instances m_train

The training instances.

m_test

protected Distribution m_test

The pruning instances.

m_id

protected int m_id

The id for the node.

Constructor Detail

ClassifierTree

public ClassifierTree(ModelSelection toSelectLocModel)

Constructor.

Method Detail

nextID

protected static long nextID()

Gets the next unique node ID.

Returns:

the next unique node ID.

resetID

protected static void resetID()

Resets the unique node ID counter (e.g. between repeated separate print types)

buildClassifier

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

Method for building a classifier tree.

Throws:

java.lang.Exception - if something goes wrong

buildTree

public void buildTree(Instances data,
                      boolean keepData)
               throws java.lang.Exception

Builds the tree structure.

Parameters:

data - the data for which the tree structure is to be generated.

keepData - is training data to be kept?

Throws:

java.lang.Exception - if something goes wrong

buildTree

public void buildTree(Instances train,
                      Instances test,
                      boolean keepData)
               throws java.lang.Exception

Builds the tree structure with hold out set

Parameters:

train - the data for which the tree structure is to be generated.

test - the test data for potential pruning

keepData - is training Data to be kept?

Throws:

java.lang.Exception - if something goes wrong

classifyInstance

public double classifyInstance(Instance instance)
                        throws java.lang.Exception

Classifies an instance.

Throws:

java.lang.Exception - if something goes wrong

cleanup

public final void cleanup(Instances justHeaderInfo)

Cleanup in order to save memory.

distributionForInstance

public final double[] distributionForInstance(Instance instance,
                                              boolean useLaplace)
                                       throws java.lang.Exception

Returns class probabilities for a weighted instance.

Throws:

java.lang.Exception - if something goes wrong

assignIDs

public int assignIDs(int lastID)

Assigns a uniqe id to every node in the tree.

graph

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

Returns graph describing the tree.

Specified by:

graph in interface Drawable

Throws:

java.lang.Exception - if something goes wrong

prefix

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

Returns tree in prefix order.

Throws:

java.lang.Exception - if something goes wrong

toSource

public java.lang.StringBuffer[] toSource(java.lang.String className)
                                  throws java.lang.Exception

Returns source code for the tree as an if-then statement. The class is assigned to variable "p", and assumes the tested instance is named "i". The results are returned as two stringbuffers: a section of code for assignment of the class, and a section of code containing support code (eg: other support methods).

Parameters:

className - the classname that this static classifier has

Returns:

an array containing two stringbuffers, the first string containing assignment code, and the second containing source for support code.

Throws:

java.lang.Exception - if something goes wrong

numLeaves

public int numLeaves()

Returns number of leaves in tree structure.

numNodes

public int numNodes()

Returns number of nodes in tree structure.

toString

public java.lang.String toString()

Prints tree structure.

Overrides:

toString in class java.lang.Object

getNewTree

protected ClassifierTree getNewTree(Instances data)
                             throws java.lang.Exception

Returns a newly created tree.

Parameters:

data - the training data

Throws:

java.lang.Exception - if something goes wrong

getNewTree

protected ClassifierTree getNewTree(Instances train,
                                    Instances test)
                             throws java.lang.Exception

Returns a newly created tree.

Parameters:

data - the training data

test - the pruning data.

Throws:

java.lang.Exception - if something goes wrong