weka.classifiers.trees
Class REPTree

java.lang.Object
  weka.classifiers.Classifier
      weka.classifiers.trees.REPTree

All Implemented Interfaces:

AdditionalMeasureProducer, java.lang.Cloneable, Drawable, OptionHandler, java.io.Serializable, Sourcable, WeightedInstancesHandler

public class REPTree

extends Classifier

implements OptionHandler, WeightedInstancesHandler, Drawable, AdditionalMeasureProducer, Sourcable

Fast decision tree learner. Builds a decision/regression tree using information gain/variance reduction and prunes it using reduced-error pruning (with backfitting). Only sorts values for numeric attributes once. Missing values are dealt with by splitting the corresponding instances into pieces (i.e. as in C4.5). Valid options are:

-M number
Set minimum number of instances per leaf (default 2).

-V number
Set minimum numeric class variance proportion of train variance for split (default 1e-3).

-N number
Number of folds for reduced error pruning (default 3).

-S number
Seed for random data shuffling (default 1).

-P
No pruning.

-T
Maximum tree depth (default -1, no maximum).

Version:

$Revision: 1.17 $

Author:

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

See Also:

Serialized Form

Nested Class Summary

protected class

REPTree.Tree An inner class for building and storing the tree structure

Field Summary

protected int	m_MaxDepth Upper bound on the tree depth
protected double	m_MinNum The minimum number of instances per leaf.
protected double	m_MinVarianceProp The minimum proportion of the total variance (over all the data) required for split.
protected boolean	m_NoPruning Don't prune
protected int	m_NumFolds Number of folds for reduced error pruning.
protected int	m_Seed Seed for random data shuffling.
protected REPTree.Tree	m_Tree The Tree object
private static long	PRINTED_NODES For getting a unique ID when outputting the tree source (hashcode isn't guaranteed unique)

Fields inherited from class weka.classifiers.Classifier

m_Debug

Fields inherited from interface weka.core.Drawable

BayesNet, NOT_DRAWABLE, TREE

Constructor Summary

REPTree()

Method Summary

void	buildClassifier(Instances data) Builds classifier.
double[]	distributionForInstance(Instance instance) Computes class distribution of an instance using the tree.
java.util.Enumeration	enumerateMeasures() Returns an enumeration of the additional measure names.
int	getMaxDepth() Get the value of MaxDepth.
double	getMeasure(java.lang.String additionalMeasureName) Returns the value of the named measure.
double	getMinNum() Get the value of MinNum.
double	getMinVarianceProp() Get the value of MinVarianceProp.
boolean	getNoPruning() Get the value of NoPruning.
int	getNumFolds() Get the value of NumFolds.
java.lang.String[]	getOptions() Gets options from this classifier.
int	getSeed() Get the value of Seed.
java.lang.String	globalInfo() Returns a string describing classifier
java.lang.String	graph() Outputs the decision tree as a graph
int	graphType() Returns the type of graph this classifier represents.
java.util.Enumeration	listOptions() Lists the command-line options for this classifier.
static void	main(java.lang.String[] argv) Main method for this class.
java.lang.String	maxDepthTipText() Returns the tip text for this property
java.lang.String	minNumTipText() Returns the tip text for this property
java.lang.String	minVariancePropTipText() Returns the tip text for this property
protected static long	nextID() Gets the next unique node ID.
java.lang.String	noPruningTipText() Returns the tip text for this property
java.lang.String	numFoldsTipText() Returns the tip text for this property
int	numNodes() Computes size of the tree.
protected static void	resetID()
java.lang.String	seedTipText() Returns the tip text for this property
void	setMaxDepth(int newMaxDepth) Set the value of MaxDepth.
void	setMinNum(double newMinNum) Set the value of MinNum.
void	setMinVarianceProp(double newMinVarianceProp) Set the value of MinVarianceProp.
void	setNoPruning(boolean newNoPruning) Set the value of NoPruning.
void	setNumFolds(int newNumFolds) Set the value of NumFolds.
void	setOptions(java.lang.String[] options) Parses a given list of options.
void	setSeed(int newSeed) Set the value of Seed.
java.lang.String	toSource(java.lang.String className) Returns the tree as if-then statements.
java.lang.String	toString() Outputs the decision tree.

Methods inherited from class weka.classifiers.Classifier

classifyInstance, debugTipText, forName, getDebug, makeCopies, setDebug

Methods inherited from class java.lang.Object

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

Field Detail

m_Tree

protected REPTree.Tree m_Tree

The Tree object

m_NumFolds

protected int m_NumFolds

Number of folds for reduced error pruning.

m_Seed

protected int m_Seed

Seed for random data shuffling.

m_NoPruning

protected boolean m_NoPruning

Don't prune

m_MinNum

protected double m_MinNum

The minimum number of instances per leaf.

m_MinVarianceProp

protected double m_MinVarianceProp

The minimum proportion of the total variance (over all the data) required for split.

m_MaxDepth

protected int m_MaxDepth

Upper bound on the tree depth

PRINTED_NODES

private static long PRINTED_NODES

For getting a unique ID when outputting the tree source (hashcode isn't guaranteed unique)

Constructor Detail

REPTree

public REPTree()

Method Detail

globalInfo

public java.lang.String globalInfo()

Returns a string describing classifier

Returns:

a description suitable for displaying in the explorer/experimenter gui

noPruningTipText

public java.lang.String noPruningTipText()

Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

getNoPruning

public boolean getNoPruning()

Get the value of NoPruning.

Returns:

Value of NoPruning.

setNoPruning

public void setNoPruning(boolean newNoPruning)

Set the value of NoPruning.

Parameters:

newNoPruning - Value to assign to NoPruning.

minNumTipText

public java.lang.String minNumTipText()

Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

getMinNum

public double getMinNum()

Get the value of MinNum.

Returns:

Value of MinNum.

setMinNum

public void setMinNum(double newMinNum)

Set the value of MinNum.

Parameters:

newMinNum - Value to assign to MinNum.

minVariancePropTipText

public java.lang.String minVariancePropTipText()

Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

getMinVarianceProp

public double getMinVarianceProp()

Get the value of MinVarianceProp.

Returns:

Value of MinVarianceProp.

setMinVarianceProp

public void setMinVarianceProp(double newMinVarianceProp)

Set the value of MinVarianceProp.

Parameters:

newMinVarianceProp - Value to assign to MinVarianceProp.

seedTipText

public java.lang.String seedTipText()

Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

getSeed

public int getSeed()

Get the value of Seed.

Returns:

Value of Seed.

setSeed

public void setSeed(int newSeed)

Set the value of Seed.

Parameters:

newSeed - Value to assign to Seed.

numFoldsTipText

public java.lang.String numFoldsTipText()

Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

getNumFolds

public int getNumFolds()

Get the value of NumFolds.

Returns:

Value of NumFolds.

setNumFolds

public void setNumFolds(int newNumFolds)

Set the value of NumFolds.

Parameters:

newNumFolds - Value to assign to NumFolds.

maxDepthTipText

public java.lang.String maxDepthTipText()

Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

getMaxDepth

public int getMaxDepth()

Get the value of MaxDepth.

Returns:

Value of MaxDepth.

setMaxDepth

public void setMaxDepth(int newMaxDepth)

Set the value of MaxDepth.

Parameters:

newMaxDepth - Value to assign to MaxDepth.

listOptions

public java.util.Enumeration listOptions()

Lists the command-line options for this classifier.

Specified by:

listOptions in interface OptionHandler

Overrides:

listOptions in class Classifier

Returns:

an enumeration of all the available options.

getOptions

public java.lang.String[] getOptions()

Gets options from this classifier.

Specified by:

getOptions in interface OptionHandler

Overrides:

getOptions in class Classifier

Returns:

an array of strings suitable for passing to setOptions

setOptions

public void setOptions(java.lang.String[] options)
                throws java.lang.Exception

Parses a given list of options.

Specified by:

setOptions in interface OptionHandler

Overrides:

setOptions in class Classifier

Parameters:

options - the list of options as an array of strings

Throws:

java.lang.Exception - if an option is not supported

numNodes

public int numNodes()

Computes size of the tree.

enumerateMeasures

public java.util.Enumeration enumerateMeasures()

Returns an enumeration of the additional measure names.

Specified by:

enumerateMeasures in interface AdditionalMeasureProducer

Returns:

an enumeration of the measure names

getMeasure

public double getMeasure(java.lang.String additionalMeasureName)

Returns the value of the named measure.

Specified by:

getMeasure in interface AdditionalMeasureProducer

Parameters:

additionalMeasureName - the name of the measure to query for its value

Returns:

the value of the named measure

Throws:

java.lang.IllegalArgumentException - if the named measure is not supported

buildClassifier

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

Builds classifier.

Specified by:

buildClassifier in class Classifier

Parameters:

data - set of instances serving as training data

Throws:

java.lang.Exception - if the classifier has not been generated successfully

distributionForInstance

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

Computes class distribution of an instance using the tree.

Overrides:

distributionForInstance in class Classifier

Parameters:

instance - the instance to be classified

Returns:

an array containing the estimated membership probabilities of the test instance in each class or the numeric prediction

Throws:

java.lang.Exception - if distribution could not be computed successfully

nextID

protected static long nextID()

Gets the next unique node ID.

Returns:

the next unique node ID.

resetID

protected static void resetID()

toSource

public java.lang.String toSource(java.lang.String className)
                          throws java.lang.Exception

Returns the tree as if-then statements.

Specified by:

toSource in interface Sourcable

Parameters:

className - the name that should be given to the source class.

Returns:

the tree as a Java if-then type statement

Throws:

java.lang.Exception - if something goes wrong

graphType

public int graphType()

Returns the type of graph this classifier represents.

Specified by:

graphType in interface Drawable

Returns:

Drawable.TREE

graph

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

Outputs the decision tree as a graph

Specified by:

graph in interface Drawable

Returns:

the graph described by a string

Throws:

java.lang.Exception - if the graph can't be computed

toString

public java.lang.String toString()

Outputs the decision tree.

main

public static void main(java.lang.String[] argv)

Main method for this class.